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cs updates on arXiv.org

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving When Is Next-Token Prediction Useful? Marginalization, Ergodicity, Mixture Identifiability, Local Sufficiency, RAG, Tools, and Programming Design and Report Benchmarks for Knowledge Work GENSTRAT: Toward a Science of Strategic Reasoning in Large Language Models Foundation Protocol: A Coordination Layer for Agentic Society AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery Hidden Human-Like Nature of Machine-Generated Texts: Theory and Detection Enhancement Self-Improving In-Context Learning Redrawing the AI Map: A Theory of Accountability Boundaries in Agentic Ecosystems Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs When Symptoms Are Not Enough: Evidence-Weighting Patterns in Large Language Model Psychiatric Screening As X, Do Y: How Persona and Task Combine in Instruction-Tuned LLMs CoReVAD: A Contextual Reasoning Framework for Training-Free Video Anomaly Detection Inconsistency-aware Multimodal Schrödinger Bridge for Deepfake Localization Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems A Fine-Tuned BERT Classifier for Personal-Letter Titles in Late-Ming and Early-Qing Collected Works A Comparative Evaluation of Structural Topic Models and BERTopic for Short, Open-Ended Survey Responses PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning The Efficiency Frontier: A Unified Framework for Cost-Performance Optimization in LLM Context Management Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models DFKI-MLT at SemEval-2026 TASK 7: Steering Multilingual Models Towards Cultural Knowledge RoboSurg-VQA: A Multimodal Benchmark for Surgical Segmentation-Aware Visual Question Answering What Training Data Teaches RL Memory Agents: An Empirical Study of Curriculum Effects in Memory-Augmented QA Dithering Defense: Adversarial Robustness of Vision Foundation Models via Multi-Level Floyd-Steinberg Dithering Millimeter-wave Imaging for Anthropometric Body Measurement Model Collapse as Cultural Evolution DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods The TIME Machine: On The Power of Motion for Efficient Perception HawkesLLM: Semantic Uncertainty Propagation in Agentic Text Simulation Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection Sparse Autoencoders Map Brain-LLM Alignment onto Cortical Semantic Topography Brain-LLM Alignment Tracks Training Data, Not Typology The Deterministic Horizon: Impossibility Results as Design Specifications for Trustworthy AI Systems Scene Reconstruction as Mapping Priors for 3D Detection CoMoGen: COntrollable MOtion Dynamics and Interactions with Mask-Guided Video GENeration A Proactive Multi-Agent Dialogue Framework for Assessing Social Language Disorder Traits in Autism Memorization Dynamics of Fill-in-the-Middle Pretraining A Reproducible Universal Dependencies-Style Pipeline for Katharevousa Greek Parliamentary Text When AI Takes Sides on Questions of Faith: Persistent Asymmetries in AI-Mediated Faith Guidance Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs Graph Alignment Topology as an Inductive Bias for Grounding Detection GazeBehavior Annotation Toolkit (GBAT): AI-powered toolkit for automatic annotation of egocentric eye-tracking and video data of child-caregiver interaction Improved Vision-to-Chart Buoy Association with Learned World-to-Image Projection Learnability-Informed Fine-Tuning of Diffusion Language Models RAS: Reflection-Augmented Scaling with In-Context Learning for Executable Cypher Query Generation VideoOdyssey: A Benchmark for Ultra-Long-Context and Omni-Modal Video Understanding EVE-Agent: Evidence-Verifiable Self-Evolving Agents Suicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations Seeing without Looking: Do Vision-Language Benchmarks Really Test Vision? Mediative Fuzzy Logic: From Type-1 Foundations to Type-2, Type-3 and Quantum Extensions ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems GEM-4D: Geometry-Enhanced Video World Models for Robot Manipulation How Far Will They Go? Red-Teaming Online Influence with Large Language Models SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research RMA: an Agentic System for Research-Level Mathematical Problems NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logic BOHM: Zero-Cost Hierarchical Attribution for Compound AI Systems GAGPO: Generalized Advantage Grouped Policy Optimization Knowledge Distillation for Low-Resource Open-source Text-to-SQL Model Query-Adaptive Semantic Chunking for Retrieval-Augmented Generation: A Dynamic Strategy with Contextual Window Expansion A Survey of Text and Speech Resources for Hausa and Fongbe: Availability, Quality, and Gaps for NLP Development Evaluating Large Language Models in a Complex Hidden Role Game AV-Master: Dual-Path Comprehensive Perception Makes Better Audio-Visual Question Answering Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning VerteNet -- A Multi-Context Hybrid CNN Transformer for Accurate Vertebral Landmark Localization in Lateral Spine DXA Images
Report on the Designing Accountable Software Systems Workshop
Catherine Albiston, Travis Breaux, Kat Dearstyne, Jane Cleland-H · 2026-06-02 · via cs updates on arXiv.org

The Workshop on Designing Accountable Software Systems (DASS) was convened in November 2024 with support from the U.S. National Science Foundation to engage a wide range of current and future stakeholders from government, academia, and industry on the cross-disciplinary topic of accountability in software systems. Over two days, attendees engaged in a series of panels, invited talks, and breakout sessions covering: (1) the dimensions of accountability, including legal compliance as well as business and societal aspects and drivers; (2) a conceptual model of the various structures needed to realize accountability; (3) the sources of legal requirements that affect software; (4) the operationalization of legal requirements in software; (5) the requirements to preserve evidence needed to conduct investigations; and (6) a range of challenges and contextual factors beyond software that affect why some accountability structures succeed, while others fail. The workshop was conducted as a collaborative systematization of knowledge that culminated in several research directions. The findings include the importance of clarifying definitions and responsibilities within accountable organizations, which can affect whether those researching accountability are making assumptions that limit the generalizability of findings. Further research was also identified as needed to study the ways to improve the translation of accountability structures into the software design process while improving engagement with stakeholders, such as legislators, regulators, business executives and system developers. Finally, a key finding was the high demands that DASS-like research projects place on interdisciplinary teams: both in terms of team formation and sustainment, as well as, the specific demands of cross-disciplinary learning that covers both research methods, research dissemination, and career development.