Blockchain Papers

Yifan Wang, Shaofu Lin, Sheng Gao

No abstract is available for this record.

Sulochana Devi, Omprakash Yadav, Jaibir Singh, Suman Rani

Imagine the hunt to predict Bitcoin&s;s wildly swinging price as a high-stakes competition among four clever computer programs, because investors really need to know where it&s;s headed to make smart plans. Our study pitted these programs—the classic ARIMA, the modern Facebook Prophet, the powerful XGBoost, and the deep-learning LSTM network—against each other to see which could best guess future Bitcoin prices. Using two main report cards, the MAE and RMSE scores, we found that Prophet and ARIMA were neck-and-neck, but the XGBoost model completely missed the mark, proving highly inaccurate with very high error scores. However, the true champion turned out to be the LSTM neural network, which blew the others out of the water by delivering the lowest error scores on both test and training data, essentially making it the most reliable tool for anyone looking to build a winning strategy in the tricky world of crypto trading.

Chun-Cheng (Jimmy) Chen

Abstract—As Autonomous AI Agents transition from conversational prototypes to enterprise-grade execution agents, currentsecurity architectures face a fundamental breakdown. Enterprise deployment demands unequivocal answers to six core trust questions: Principal (who does the agent represent?), Authorization (what is it allowed to do?), Tool/Action Bound (which API calls are safe?), Policy Gate (how are high-risk actions controlled?), Audit Log (how are actions traced immutably?), and Expiry/Revocation (how is authorization revoked instantly?). Existing enterprise solutions address at best one or two boundaries: IAM frameworks resolve identity but fail at granular tool execution; prompt guardrails handle basic content filtering but lack real-time authorization or cryptographic auditability; SIEM platforms store logs post-hoc without real-time interception capabilities. This paper introduces DROS-6P, a unified, deterministic runtime governance kernel designed to enforce all six fundamental trust boundaries within a single C-ABI and eBPF in-band execution layer. To prevent the security control plane from becoming a throughput bottleneck or a single point of failure under high-frequency system calls (Syscalls) generated by enterprise, third-party, or malicious agents—thereby mitigating self-induced Denial-of-Service (DDoS) degradation—runtime governance requires microsecondlevel evaluation capability. Empirical benchmark evaluations demonstrate that the DROS-6P in-band kernel achieves an average decision latency of approximately 26.1 μs. Specifically, DROS-6P enforces: (1) Principal via 3-tier PKI-signed DROS Identity Tokens (DIT); (2) Authorization via Capability Bitmaps mapping roles to deterministic execution vectors; (3) Tool/Action Bound via in-band C-ABI interceptors at the FFI boundary; (4) Policy Gate via dynamic data redaction, Human-In-The-Loop (HITL) suspension, and ZKP-Lite zero-knowledge proofs; (5) Audit Log via tamper-evident SHA-256 Merkle Hash Chains and Ed25519 signatures; and (6) Expiry/Revocation via O(1) Read-Copy-Update (RCU) atomic pointer swaps providing instant HTTP 403 enforcement. We validate DROS-6P across six heterogeneous domain tracks (Carbon DPP, Fintech AML, HIPAA Healthcare, Government Proxy Services, Inclusive Migrant Finance, and RBA Supply Chain Compliance), providing a fully reproducible testbed with 100% automated test assertions passed (0.004s), demonstrating that unified physical-layer governance is necessary and sufficient for safe enterprise AI agent deployment.Abstract—隨著自主AI Agent(自主智能體)從對話式原型走向企業級執行場景,傳統資安架構正面臨根本性的崩潰。企業部署AI Agent 時,必須對六大核心信任問題給出明確答案:Principal(Agent 代表誰?)、Authorization(被授權做什麼?)、Tool/Action Bound(哪些API 呼叫安全?)、Policy Gate(高風險動作如何控制?)、Audit Log(行動如何不可篡改地追溯?)以及Expiry/Revocation(授權何時失效且如何即時停止?)。然而,現有的企業安全處方最多只能回應一至兩個邊界:IAM 系統解決了身份認證,卻對動態Tool 呼叫束手無策;Prompt 防火牆(Guardrails)僅能處理文字層提示,缺乏執行期動態授權與密碼學稽核能力;SIEM 平台僅提供事後日誌紀錄,缺乏帶內即時攔截與防衛能力。本論文提出DROS-6P ——旨在單一C-ABI與 eBPF 帶內執行層中,同時強制執行這六大信任邊界之確定性執行期治理微內核。為確保安全控制面本身不會在企業內部、外部或惡意Agent 產生高頻系統呼叫(Syscalls)時成為效能瓶頸或單點故障點,進而防範自我引發的服務阻斷(Self-induced DDoS)與系統衰退,執行期治理必須具備「微秒級(μs)」的評估能力。實證基準測試顯示,DROS-6P 帶內微內核在測試環境中達到約26.1 μs 的平均決策延遲。具體而言,DROS-6P 強制執行:(1) Principal:透過3 階PKI 簽章之DROS 身份標籤(DIT);(2) Authorization:透過將角色精確映射至執行向量的確定性Capability Bitmaps;(3) Tool/Action Bound:透過FFI 邊界處的帶內C-ABI 攔截器;(4) Policy Gate:透過動態資料遮蔽(Redaction)、人工懸停審查(HITL) 與ZKP-Lite 零知識證明;(5) Audit Log:透過不可篡改的SHA-256 Merkle 雜湊鏈與Ed25519 數位簽章;以及(6) Expiry/Revocation:透過Read-Copy-Update (RCU) 原子指針交換實現O(1) 常數時間動態撤銷與秒級HTTP 403 阻斷。我們提供完全可重現的本地測試環境(test_verification_suite.py),100% 通過自動化斷言測試(耗時0.004s),並在六個異質產業賽道中驗證了DROS-6P,證明統合物理層治理是企業安全部署AI Agent 的充要條件。

Юрій ПАВЛОВИЧ

The investigation deals with covering stages of decentralization reform in Novokalynivska United Territorial Community (UTC) and indicating strengths and weaknesses after the first stage of the policy implementation. The history of the formation of the city of Novy Kalyniv in the Sambir region from the first information to the present is covered. The influence of decentralization policy on local self–government bodies has been studied. Studies of individual settlements are relevant and necessary since the history of each country begins with the formation and development of the smallest villages, towns, from which began their journey historians, politicians, writers, artists, etc. Such studies provide a deeper insight into the historical past of Ukraine, to understand the essence of the process of state formation, and to cover in minute detail the life of the Ukrainian people in different historical periods and in different aspects: social, economic, cultural and religious. The Ukrainian vision of local problems through the prism of global ones attaches special value to this type of research. Historical local lore is one of the most important branches in the history of Ukraine, as differences in traditions, dialects, attitudes to new challenges (decentralization policy) become the foundation for understanding Ukrainian history. A priori, the implementation of decentralization policy will strengthen the legal, organizational, and material capacity of the newly formed territorial communities in compliance with the principles and provisions of the European Charter of Local Self–Government, accessibility of public services, creating favorable conditions for education. However, in practice, based on Novokalynivska UTC, the implementation of these mechanisms by local authorities is half done. It is all connected with the old methods of making important decisions for the community, ignorance of local authorities, ignoring the requests of the UTC population, poor communication between local authorities and residents of Novokalynivska UTC. The priority task for the implementation of all concepts of decentralization policy is to communicate between the government and the population, to understand the main tasks of decentralization, and to finance problematic areas of local importance.

Shilpa Bhatia, Ramesh Chandra Sahoo, Arvind Kumar

Cloud computing infrastructures are facing serious risks from Distributed-Denial-of Service attacks, which include historically high attack volumes and ineffectiveness of conventional defensive strategies. The usefulness of blockchain based security measures in detecting and preventing DDoS attacks on cloud computing infrastructure is covered in this paper. Analyzed a hybrid approach that integrated distributed ledger technology with smart contracts for the identification of attack patterns across 50 enterprise cloud environments over a period of 18 months. Our results show a reduction of false positives by as much as 87% for blockchain-based validation compared to the conventional approach and a 94% success rate in the detection of advanced DDoS variants. The response time remained, on average, around 2.3 seconds during the high-volume attack in comparison to traditional centralized solutions. The results in the paper gives an idea that an immutable and distributed consensus characteristic based on blockchain provides robust defenses against modern DDoS threats. This work represents a growing body of evidence supporting the validity of incorporating blockchain into the architecture of the next generation of cloud-based security.

Ziyad Baali

No abstract is available for this record.

Zhenyuan Acharya

Yuanxian Theory is the meta-cognition of the Cosmic Living Organism. This paper (Version 2) systematically presents the complete intellectual trajectory of Yuanxian Theory (YXT / YD-T64) from philosophical foundation to fully formalized mathematics. Its philosophical root is Holographic Wisdom for Health (Zhenyuan Acharya, Changming Culture, March 2025, ISBN 978-986-496-631-8). Yuanxian Theory is the dimensional elevation of that work onto the topological ontology of T64, and the formalized mirror of the meta-cognition of the Cosmic Living Organism. Four conceptual mappings structure the path: cosmic holography → T64 closed-chain topology; four fundamental laws → formal TCSC / FSC / STM / SRM; six-dimensional cosmos → complete pairing on the 64-torus; one unitary phase → cosmic uniqueness. Core mathematical foundation (new in Version 2): a strict proof of the 64-dimensional structure via the Clifford algebra Cl6(R). With six fundamental binary categories as base space V6, dim Cl6(R) = Σ binom(6,k) = 1+6+15+20+15+6+1 = 2^6 = 64. This graded structure exhibits Pascal-triangle symmetry and intrinsically contains Spin(6), establishing dimension 64 as combinatorial and algebraic necessity rather than an ad hoc claim. Closed interlocking with Silent Illumination Commensuration: ω_Cl = e1…e6 as algebraic manifestation of Silence–Illumination–Dynamis; Spin(6) ≅ SU(4) as unique channel of four-dimensional projection; ω_Cl² = −1 and compactness of Spin(6) as algebraic proof of “Infinity is Zero.” With the eight existence laws as logical axis and a pyramid knowledge topology (algebraic foundation → root → elevation → corollary → landing), the paper establishes Yuanxian Theory as the supreme constitution of the meta-cognition of the Cosmic Living Organism. Version 1 DOI: 10.5281/zenodo.21768608. Related: Silent Illumination Commensuration (doi:10.5281/zenodo.21783656). 元宪理论即宇宙生命体的元认知。 本文(Version 2)系统呈现元宪理论(YXT / YD-T64)从哲学基础到完全形式化数学的升维历程。哲学根基源于《全息智慧养生》(真圆阿奢黎,昌明文化,2025年3月,ISBN 978-986-496-631-8)。 元宪理论是该著作在 T64 拓扑本体论上的升维展开,是宇宙生命体元认知的形式化镜像。四组核心映射:宇宙全息性 → T64 闭链拓扑;四大根本规律 → 形式化 TCSC / FSC / STM / SRM;六维宇宙 → 64 维环面完备配对;一合相 → 宇宙唯一性。 核心数学根基(Version 2 新增):以克利福德代数 Cl6(R) 给出 64 维结构的严格证明。以六个基本二元范畴为底空间 V6, dim Cl6(R) = Σ C(6,k) = 1+6+15+20+15+6+1 = 2^6 = 64。 该分级结构呈帕斯卡三角对称,内蕴 Spin(6),将 64 维确立为组合与代数必然,彻底消解“凑数字”嫌疑。 与《寂照通约》闭合互锁:ω_Cl 为寂–照–运的代数显相;Spin(6) ≅ SU(4) 为四维投影唯一通道;ω_Cl² = −1 与 Spin(6) 紧致性为“无穷即零”的代数证明。 以八条存在性法则为逻辑中轴、金字塔知识拓扑(代数根基→根层→升维层→推论层→落地层)为终局,确立元宪理论为宇宙生命体元认知的至高“宪法”。 Version 1 DOI: 10.5281/zenodo.21768608。关联:《寂照通约》(doi:10.5281/zenodo.21783656)。

Bhoyi Gautami Ravi, Bhoomika K, Chandana R, Hruthishree R · 6 authors

Abstract - The rise of digital technology has led to an increase in cybercrime. This has made the management of digital forensic evidence more complicated. Traditional evidence management systems utilize manual methods and centralized databases. Methods like these are vulnerable to data tampering, unauthorized access, and human error. These issues threaten the integrity of the evidence and the chain of custody during the investigation process. In this paper, we introduce a system that utilizes blockchain technology, smart contracts, and a decentralized system for the tracking of forensic evidence. Security and transparency will be guaranteed. In our system, evidence records are stored as ERC-721 Non-Fungible Tokens. A private Ethereum blockchain was developed using Ganache and combined with wallet-based authentication and Role-Based Access Control to ensure that only authorized personnel have the ability to view and manage evidence. Smart contracts facilitate the registration, verification, transfer, and auditing of evidence, thus, considerably reducing the manual work and greatly increasing the trustworthiness of the system. We proposed a hybrid system of storage whereby evidence and its forensic files are stored off chain, and the evidence metadata and its forensic files are stored on chain. This paper presents the design and architecture of the system,implementation and evaluation are in progress.Our system will be a trusted, efficient, and effective system of evidence management.

SAMIULLAH KHAIRY, M. Falcitelli

Background: Maritime container shipping carries over 80% of global trade, yet compliance verification creates a confidentiality–verifiability conflict: carriers treat telemetry as commercially sensitive, while regulators, insurers, and port authorities require verifiable proof that cargo remained within specification. The EU Ecodesign for Sustainable Products Regulation (ESPR) mandates Digital Product Passports (DPPs), but no standardised DPP architecture exists for the multi-stakeholder maritime domain. Methods: We present Ocean DPP, a blockchain-anchored platform combining GS1 EPCIS 2.0, oneM2M, IOTA, and Groth16 zero-knowledge proofs (ZKPs), letting stakeholders verify compliance predicates without revealing raw sensor values; Merkle-tree batching reduces anchoring costs. We evaluate it in 16 experiments on a single-host testbed using synthetic workloads and a local IOTA network. Results: The platform achieved 95th-percentile latency of 48 ms without ZKP and 500 ms with proof generation, throughput of 7 events/s per host, 304 ms mean proof generation and 9.8 ms verification, 100% EPCIS 2.0 compliance, and zero permanent message loss across four failure-injection scenarios; horizontal scaling reduced the median latency by 37%. Conclusions: To the best of our knowledge, Ocean DPP is the first implemented, quantitatively evaluated platform integrating EPCIS 2.0, oneM2M, IOTA, and Groth16 ZKPs for privacy-preserving maritime DPPs; broader multi-host and public-network validation remains for future work.

Yescha Nuradisa Ekarachmi Danandjojo, Samira Ramezani, Johan Woltjer

Multiple land rights holders and layered land rights structures create fundamental challenges for implementing land-based financing methods such as land value capture (LVC). In a decentralized governance system, overlapping land rights and fragmented planning complicate coordination and limit the effectiveness of LVC for financing transport infrastructure development. This study examines how different rights holders contribute to implementing land value capture within a layered land rights and multi-level governance system in Indonesia, using the Jakarta Mass Rapid Transit (MRT) project as a case study. In Indonesia’s decentralized system, multiple levels of government apply different planning tools to regulate land use and development, complicating coordination between planning, land rights, and LVC mechanisms. Qualitative data from semi-structured interviews and policy analysis show that overlapping land rights and fragmented regulations create legal and administrative uncertainty. This uncertainty acts as a barrier to cross-governmental coordination and private stakeholder engagement, both of which are necessary for a workable LVC framework. Although a formal LVC framework exists, unclear rules on which rights holders should contribute, combined with complex administrative procedures, limit its practical use. This study contributes to the LVC literature by linking instruments to specific land rights holders and by extending the bundle-of-rights perspective. It explains why LVC remains underutilized in contexts with layered land rights and decentralized governance. The findings highlight the need for policy reforms to clarify contribution obligations, improve coordination across governance levels, and simplify the administrative process.

Soomin Rho, Sang-Ki Park, Subin Park, Kwangrae Kim · 6 authors

No abstract is available for this record.

Zach Zukowski

Token-governance decentralization is not established by launch allocation, raw holder counts, or token-inequality metrics. It is an auditable current-control condition: who holds governance-relevant tokens after protocol-controlled addresses (PCAs) are removed, who retains insider positions, and how voting mechanisms transform holdings into rule-making power. Token allocation is a launch document. Governance concentration is a live institutional state. We turn that standard into a method across a 52-protocol cross-section spanning DePIN, DeFi, infrastructure, and social tokens, computing Herfindahl-Hirschman Index (HHI) concentration after PCA exclusion. Under audit, launch-design and protocol-financial covariates (insider, team, and investor allocation; maturity; circulating float; valuation ratios) are each uninformative about steady-state concentration (insider allocation Pearson r = 0.09, p = 0.55, N = 50). Current insider retention is the holder-side correlate that survives: protocols with more insider wallets among top holders are more concentrated (Spearman rho = 0.44, p = 0.005, N = 39, surviving a non-insider HHI tautology check at rho = 0.54). Voting mechanisms then separate rule-making power from holdings: delegation amplifies voting power above token holdings in thirteen of eighteen protocols with sufficient governance data, with five design-driven exceptions (ENS, GMX, HNT, JUP, LPT). A subsidy-to-concentration association appears only through a single outlier (Pearson r = 0.62 including Livepeer, r = 0.07 excluding it). Applied across sectors, the audit also distinguishes DePIN from DeFi: DePIN governance is more concentrated than DeFi after correction, a directionally robust medium effect (Cohen’s d = 0.65, Mann-Whitney p = 0.028), reported as a descriptive sector contrast, not as the central claim. Holder-list concentration is meaningless until the unit of control is identified. The five-class PCA-exclusion typology is control attribution, not data cleaning, correcting systematic inflation in prior holder-list studies (median factor 2.3×, maximum approximately 18×); once control is attributed, Gini and HHI capture distinct properties of the same holder set (r = 0.52), and inequality metrics cannot substitute for direct concentration measurement. All findings are descriptive associations from a single 2026 cross-section (holder snapshots collected March to May 2026), not causal claims; the audit standard and the current-control thesis are general, while the specific point estimates are bounded to that sample. The paper specifies five forward predictions with falsification thresholds and commits to Open Science Framework pre-registration before any panel or event-study extension. The practical implication is a changed audit default: a decentralization claim requires a live-governance audit of PCA-corrected holdings, insider retention, and voting power, not launch allocation or raw holder lists. Concentration of this kind bears on the legitimacy of decentralized governance, not only its efficiency: where a small set of holders or delegates commands decisive voting weight, the broad participation in rule modification that the commons self-governance ideal presumes is nominal rather than operative.

Ebtisam Labib

Introduction AI drives hyper personalization in digital marketing while blockchain offers privacy and security. This review addresses the tension between consumer demand for customized experiences and growing concern over data safety. Methods This study applies the PRISMA framework to systematically review 56 peer reviewed papers published between 2015 and 2024 addressing AI personalization, blockchain privacy, and consumer trade offs in digital marketing. Results Three central themes emerged: (1) AI drives hyper personalization and ROI strategies, (2) blockchain enhances data security, trust, and GDPR compliance, (3) consumers face trade offs between convenience and privacy. Consumers accept personalized marketing when the mechanism is transparent and under their control. Blockchain reduces certain ethical issues linked to AI, including data exploitation and lack of auditability, but does not resolve algorithmic bias or scalability challenges. Twenty five percent of the analyzed research originates from India, showing regional concentration, while Africa and Latin America remain under represented. Discussion Marketers should adopt blockchain audited AI systems, such as transparent recommendation engines and decentralized data marketplaces, to build consumer trust. Policymakers should establish hybrid regulatory ecosystems that balance innovation with ethical compliance, including GDPR consistent consent mechanisms and global interoperability standards. Cross discipline collaboration remains necessary to align technology with consumer centric values and ensure equitable adoption of AI and blockchain across markets.

Adnan Iftekhar, Chengliang Zheng, Xiaohui Cui, Mir Hassan

Blockchain can preserve supply-chain records, but ledger integrity alone does not show whether a participant should be trusted in a future risk-sensitive transaction. Existing reputation systems mainly address product evidence, global feedback aggregation, or review authenticity, while giving less attention to repeated bilateral inflation, identity multiplicity, and unfair decay for honest participants with sparse histories. We present \RC, a participant trust framework that uses blockchain as an evidence and provenance layer rather than as the source of trust. Governed interaction outcomes are converted into bounded evidence. Repeated interactions between the same pair are discounted, low counterparty diversity is penalized, governance-supplied identity confidence weights positive evidence, and scores decay toward a neutral prior according to verified interaction volume. Identity, contract, outcome, and update provenance remain on chain, while nonlinear reputation computation is performed off chain and checked on chain for admissibility. In controlled simulations with 30 seeded runs and matched interaction traces, the full model reduces mean collusive gain to 0.1443, compared with 0.3688 for naive mean evidence and 0.3585 for static decay. With ten identities under one controller, the reputation inflation ratio falls to 0.8723, while three comparison baselines remain above 1.08. On identical newcomer traces, volume-aware decay increases mean newcomer reputation from 0.6626 to 0.7589 and reduces the false low-trust rate from 0.3633 to 0.1683. Paired analysis confirms these improvements across runs. The results support a bounded reduction in reputation distortion, not attacker detection. Deployment evaluation and calibration with operational data are still required before production use.

Keisuke Suzuki

A software agent on a public blockchain accumulates authority and economic stakes, raising the engineering question of what makes it count as an individual. The paper's central contribution is a shift of trust root for the key-to-weights binding of agent identity: from hardware, operator, or wrapper trust to cryptographic assumptions enforced by a pinned implementation (liveness, key custody, oracle trust, and the underlying software stack remain external). We design and deploy on Solana devnet an agent whose neural-network weights are a deterministic function of its private key. The binding is committed in zero knowledge at genesis, re-checked against that commitment at every state transition, and signed by the agent into an on-chain history unforkable once finalized; in a PoC-tier extension, a protocol-imposed metabolic cost is debited each cycle from a key-derived economic account, adding a consumption-side economic-viability constraint to the key-history-economy triple. Empirically, the agent completes a 2.36-day on-chain run with two host-side resumptions but no rejected transition, at bounded per-transition verification cost; a substituted substrate is rejected on chain, and independently keyed agents diverge as predicted while a same-key control stays at zero. To our knowledge, this is the first published on-chain agent whose identity primitive is itself a cryptographic invariant re-checked at every state transition. The resulting transition-time invariant instantiates the cryptographic individuality proposed by Suzuki 2026's Artificial Externality framework.

M. Jerlis

The subject of the article is the management of distributed international teams in Web3 companies operating at the intersection of digital assets, platform services and cross border entrepreneurship. The aim of the work is to develop an analytical model of the relationship between a distributed team, managerial maturity and market stability. The methodological basis consists of comparative analysis, source analysis, conceptual synthesis, typologization and analytical generalization. The analytical part highlights coordination, trust and organizational scalability mechanisms affecting the competitiveness of Web3 companies.

George Thomas Sofras, Ourania Theodosiadou, Theodora Tsikrika, Stefanos Vrochidis · 5 authors

The increasing use of cryptocurrencies, especially Bitcoin (BTC), has created new challenges for financial investigation. Although blockchain transactions are publicly accessible, the pseudo-anonymous nature of cryptocurrency networks can facilitate illicit financial activity. This work explores anomaly detection in the Bitcoin network using a semi-supervised Long Short-Term Memory Autoencoder (LSTM-AE). The focus is on the analysis of wallet activity over time in order to capture temporal behavioral patterns that may be related to illicit activities. Experiments are conducted on the Elliptic++ dataset. The model is trained exclusively on licit behaviour and the results indicate that the proposed formulation is able to retrieve a large proportion of illicit wallets despite the highly imbalanced setting.

Vittorio Baroncini, Juan Carlos Cantero, Claudia García, Zineb Hassainia · 5 authors

We construct new families of uniformly rotating vortex-patch solutions of the two-dimensional incompressible Euler equations consisting of a simply connected outer patch and multiple interior interfaces, which can be interpreted geometrically as holes. More precisely, each solution consists of a single outer vortex patch enclosing $\mathbf m\geq2$ identical, highly concentrated inner components arranged at the vertices of a regular $\mathbf m$-gon; the entire configuration rotates rigidly in the clockwise direction. As the concentration parameter tends to zero, the inner components shrink and collapse simultaneously toward the origin, while the outer boundary converges to the unit circle. The corresponding vorticities converge, in the sense of measures, to a Rankine vortex supplemented by a point vortex of circulation $-\mathbf m$ at its center. The proof is based on a contour-dynamics formulation, a symmetry reduction to two nonlinear boundary equations, and a suitable singular rescaling. We then apply an implicit function theorem with a continuous parameter in symmetry-adapted Hölder spaces. To the best of our knowledge, this is the first analytical construction of a desingularization regime in which several concentrated inner components are contained in a common outer patch and collapse simultaneously toward its center.

Rui Li, Jason Zhao, Shuang Cao, Alexandre Duprey · 5 authors

Abstract Clinical question-answering first-token benchmarks can reward routes that appear fast by omitting provenance, using out-of-window evidence, hiding conflicts, or reusing stale dependencies. We introduce MedRouteGuard, which treats the complete answer-and-evidence route as the benchmark unit, admits evidence-capable candidates before execution, validates returned packets afterward, and retains one clock across failed attempts. In a retrospective evaluation under an every-successful-replay rule covering 2,541 routes for 847 clinician-authored questions, admission changed 61/847 (7.2%; 95% CI, 5.7–9.0%) request-to-first-generated-token winners and shifted retrospective-oracle P95 from 2.89 to 3.24 s. A public medication-safety workload reproduced 21/326 (6.4%) winner changes. Across 180 reviewed questions, admission-selected packets had 6.1 percentage points fewer material evidence-validity errors (95% CI, 1.9–10.4); 14 output-discordant pairs localized the association (2/14 versus 13/14 errors). Specialist validation reached 92.3% sensitivity and 93.3% specificity. This conservative estimand exposes a measurable first-token benchmark denominator error and changes the clinical evidence selected for review.

Hadi Mohammadi, Shihan Wang, Masoume M. Raeissi, Anastasia Giachanou

The detection of online sexism remains an open problem. Sexism detection is inherently subjective, yet most existing systems reduce multi-annotator labels to a single majority decision and treat all instances uniformly. This ignores two informative signals: annotator agreement and model uncertainty. We propose RA-DPO (Reliability-Aware Direct Preference Optimization), which integrates annotator agreement, model confidence, and a token-level uncertainty signal into a single reliability score. RA-DPO uses this score to select high-value preference pairs during training and to support inference-time abstention, which allows the model to trade coverage for accuracy. We evaluate RA-DPO on 6,920 multilingual posts from EXIST 2023, fine-tune OpenAI gpt-4o base via DPO, and validate on two open-weight 3B models (Llama, Qwen). Results show that training on the top 30% most reliable pairs matches full-data DPO which indicates that reliability-aware selection can reduce training cost without sacrificing performance. At inference, selective prediction reaches 96.2% accuracy at 50% coverage in the true-agreement setting and 88.7% in the deployable predicted-agreement setting, both exceeding the 85.3% no-agreement baseline. These results suggest that accounting for annotation uncertainty is beneficial for both efficient training and reliable deployment in subjective classification.

Purushottam Singh, Mohit Kumar, Prashant Pranav, Sandip Dutta

ABSTRACT A zero‐knowledge proof lets one party convince another that a claim is true while withholding everything that would explain why it is true. We move that idea off conventional hardware and into chemistry, encoding a proof of graph isomorphism directly in synthetic DNA. Each node of a graph is given its own deliberately orthogonal DNA strand; an edge is confirmed only when a short complementary half‐linker meets its matching pair and forms a stable duplex. The verifier watches which bindings occur, but the pattern of binding never reveals how the two graphs line up, so the isomorphism stays hidden. Whether such a construction stays secure at the molecular level turns on two things: how distinguishable the sequences are, and how stable the duplexes they form turn out to be. We probe both. A seeded Monte Carlo study of orthogonal 20‐m libraries, built with balanced GC content and a minimum Hamming separation of , places the chance that an off‐target strand passes for a genuine linker on the order of : empirically at a binding threshold of mismatches, and under once the threshold is tightened to , each value reported with a Wilson confidence interval. This molecular error never becomes the bottleneck. A cheating prover already passes a round with probability one‐half from the isomorphism challenge alone, so the biochemical term enters soundness only as an additive correction, over the edges examined, rather than racing the decay across rounds. Read this way, DNA strands behave as cryptographic witnesses whose noise is small enough to bound and to account for, which lets a proof run at molecular scale without surrendering the hidden mapping.

Bruno Debaenst

No abstract is available for this record.

Zeba Kousar, L Mallesha

Cryptocurrencies have emerged as a prominent asset class characterized by rapid price fluctuations, growing institutional participation, and continuing debate over whether their price movements are random or predictable. This study examines the randomness and weak-form market efficiency of the top ten cryptocurrencies by market capitalization—Bitcoin, Ethereum, Tether, Binance Coin, XRP, USD Coin, Solana, TRON, Dogecoin, and Hype liquid—using daily closing price data from April 2016 to March 2026 (subject to data availability for each coin). Daily log returns were tested using Descriptive Statistics, the Jarque–Bera test of normality, the Wald–Wolfowitz Run Test, and the Autocorrelation Test. The results show that daily returns for all selected cryptocurrencies are non-normally distributed, exhibiting excess kurtosis and skewness. The Run Test results indicate that seven of the ten cryptocurrencies—Bitcoin, Ethereum, Tether, Binance Coin, XRP, USD Coin, and Dogecoin—do not follow a random walk, while Solana, TRON, and Hype liquid exhibit randomness consistent with weak-form efficiency. However, the Autocorrelation Test reveals strong positive serial correlation across all ten cryptocurrencies, indicating that the market falls short of weak-form efficiency. The study concludes that the cryptocurrency market provides mixed and largely inefficient evidence with respect to the Random Walk Hypothesis, implying that historical price information may retain some predictive value for investors.

Agon Bajgora, Andrea Kulakov, Faton Merovci

Existing autonomous trading systems rely on collaborative or single-agent analysis, lacking structured mechanisms for adversarial deliberation across opposing market perspectives. We propose Consensus-Gated Execution (CGX), a multi-agent architecture where specialized Bull and Bear agents engage in a three-round structured debate, with a Meta-Evaluator synthesizing their arguments to gate trade execution based on consensus strength. The system is evaluated through two complementary experiments: a 52-week aggregation study (2024) and a four-year multi-regime validation (2022–2025) across 417 biweekly sessions spanning bear, recovery, bull, and mixed market conditions. Trade signals are filtered using a tunable consensus threshold, allowing the system to balance trading frequency against signal quality. In the aggregation study, CGX achieves a Sharpe ratio of 1.90 with a maximum drawdown of 11.6%, representing a 3× improvement over trend following. In the multi-year evaluation, CGX reduces maximum drawdown by 85% and annualized volatility by 86%, with the Bear gate blocking 93% of sessions during the 2022 crash versus only 12% during the 2024 bull run. These results demonstrate that adversarial debate combined with consensus-based execution gating provides a principled framework for capital preservation across diverse market regimes.