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cs.AI updates on arXiv.org

Detecting Safety Violations Across Many Agent Traces C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks Discourse Diversity in Multi-Turn Empathic Dialogue Evaluating Cooperation in LLM Social Groups through Elected Leadership SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems Legal2LogicICL: Improving Generalization in Transforming Legal Cases to Logical Formulas via Diverse Few-Shot Learning Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents A Triadic Suffix Tokenization Scheme for Numerical Reasoning Synthius-Mem: Brain-Inspired Hallucination-Resistant Persona Memory Achieving 94.4% Memory Accuracy and 99.6% Adversarial Robustness on LoCoMo Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Quantization Dominates Rank Reduction for KV-Cache Compression Anthropogenic Regional Adaptation in Multimodal Vision-Language Model Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories Do LLMs Know Tool Irrelevance? Demystifying Structural Alignment Bias in Tool Invocations The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method CocoaBench: Evaluating Unified Digital Agents in the Wild MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis Use of AI Tools: Guidelines to Maintain Academic Integrity in Computing Colleges Efficient Training for Cross-lingual Speech Language Models Guardrails Beat Guidance: A Large-Scale Study of Rules, Skills, and Persistent Configuration for Coding Agents Towards Proactive Information Probing: Customer Service Chatbots Harvesting Value from Conversation Shared Emotion Geometry Across Small Language Models: A Cross-Architecture Study of Representation, Behavior, and Methodological Confounds A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities Uncertainty-Aware Web-Conditioned Scientific Fact-Checking Min-$k$ Sampling: Decoupling Truncation from Temperature Scaling via Relative Logit Dynamics When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies When Verification Fails: How Compositionally Infeasible Claims Escape Rejection Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution Mem$^2$Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis Speaking to No One: Ontological Dissonance and the Double Bind of Conversational AI Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series TInR: Exploring Tool-Internalized Reasoning in Large Language Models Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents Learning and Enforcing Context-Sensitive Control for LLMs Efficient Process Reward Modeling via Contrastive Mutual Information Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment NSFL: A Post-Training Neuro-Symbolic Fuzzy Logic Framework for Boolean Operators in Neural Embeddings Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance Calibration Collapse Under Sycophancy Fine-Tuning: How Reward Hacking Breaks Uncertainty Quantification in LLMs Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models LLMs Should Incorporate Explicit Mechanisms for Human Empathy AI Patents in the United States and China: Measurement, Organization, and Knowledge Flows ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization Thinking Fast, Thinking Wrong: Intuitiveness Modulates LLM Counterfactual Reasoning in Policy Evaluation A Progressive Training Strategy for Vision-Language Models to Counteract Spatio-Temporal Hallucinations in Embodied Reasoning Cooperation in Human and Machine Agents: Promise Theory Considerations CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs PEMANT: Persona-Enriched Multi-Agent Negotiation for Travel From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation VeriSim: A Configurable Framework for Evaluating Medical AI Under Realistic Patient Noise CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning CWCD: Category-Wise Contrastive Decoding for Structured Medical Report Generation TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection Beyond Monologue: Interactive Talking-Listening Avatar Generation with Conversational Audio Context-Aware Kernels ClawVM: Harness-Managed Virtual Memory for Stateful Tool-Using LLM Agents VeriTrans: Fine-Tuned LLM-Assisted NL-to-PL Translation via a Deterministic Neuro-Symbolic Pipeline Zero-shot World Models Are Developmentally Efficient Learners From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences Gypscie: A Cross-Platform AI Artifact Management System TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale AI Organizations are More Effective but Less Aligned than Individual Agents Dead Cognitions: A Census of Misattributed Insights STARS: Skill-Triggered Audit for Request-Conditioned Invocation Safety in Agent Systems The Amazing Agent Race: Strong Tool Users, Weak Navigators A Dual-Positive Monotone Parameterization for Multi-Segment Bids and a Validity Assessment Framework for Reinforcement Learning Agent-based Simulation of Electricity Markets SVSR: A Self-Verification and Self-Rectification Paradigm for Multimodal Reasoning Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models Edu-MMBias: A Three-Tier Multimodal Benchmark for Auditing Social Bias in Vision-Language Models under Educational Contexts Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision PoreDiT: A Scalable Generative Model for Large-Scale Digital Rock Reconstruction MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
CTI4AI: Threat Intelligence Generation and Sharing after Red Teaming AI Models
Chuyen Nguyen, Caleb Morgan, Sudip Mittal · 2022-08-16 · via cs.AI updates on arXiv.org

As the practicality of Artificial Intelligence (AI) and Machine Learning (ML) based techniques grow, there is an ever increasing threat of adversarial attacks. There is a need to red team this ecosystem to identify system vulnerabilities, potential threats, characterize properties that will enhance system robustness, and encourage the creation of effective defenses. A secondary need is to share this AI security threat intelligence between different stakeholders like, model developers, users, and AI/ML security professionals. In this paper, we create and describe a prototype system CTI4AI, to overcome the need to methodically identify and share AI/ML specific vulnerabilities and threat intelligence.