AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSamsone: A Family of Open Small Audio Language Models for On-Device Inference
arXiv:2609.21666v1 Announce Type: cross Abstract: The success of Large Audio Language Models has driven the development of massive multimodal networks exceeding billions of parameters. However, the demand for privacy-pre…
- arXiv cs.AIresearchFrom Code Archival to Knowledge Graph: Bridging Software Heritage, COAR Notify and Wikidata
arXiv:2609.21667v2 Announce Type: replace-cross Abstract: Software is a first-class scientific object, yet validated links between source code and the scholarly record remain largely absent from the Linked Open Data (LOD…
- arXiv cs.AIagentsCIPL: A Channel-Aware Framework for Recoverable Privacy Leakage in LLM Agents
arXiv:2609.21686v1 Announce Type: cross Abstract: Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it difficult to distinguish…
- arXiv cs.AIresearchTERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor
arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-control decisions, or trig…
- arXiv cs.AIresearchCIBuzzBench: A Benchmark for Cross-Lingual Understanding of Chinese Internet Buzzwords
arXiv:2609.21722v1 Announce Type: cross Abstract: Chinese social media has generated a vast and continually evolving lexicon of internet buzzwords whose meanings are often non-literal and deeply rooted in local cultural…
- arXiv cs.AIresearchBalanced Prompt Adaptation against Entropy-Induced Collapse for Test-Time Binary Segmentation
arXiv:2609.21743v1 Announce Type: cross Abstract: Entropy minimization is a standard objective for test-time adaptation (TTA), but it can fail in imbalanced binary segmentation. Unlike image classification, dense segment…
- arXiv cs.AIresearchForceTwin: Physics-informed Digital Twins for Robotic Manipulation from Instrumented Human Interaction
arXiv:2609.21751v1 Announce Type: cross Abstract: Manipulating objects requires understanding not only their motion, but also the physical properties that determine it. For articulated objects, these include inertia, fri…
- arXiv cs.AIagentsAn Agentic Just-in-Time Adaptive Intervention System for Personalized Sleep Support: Proof-of-Concept Study with N of 1 Data
arXiv:2609.21805v1 Announce Type: cross Abstract: Background: Just-in-time adaptive interventions (JITAIs) can use behavioral data to adapt support to changing contexts, but many rely on predefined rules and manual confi…
- arXiv cs.AIresearchMatrix AdaGrad: Row-wise and Column-wise Adaptive Subgradient Methods
arXiv:2609.21815v2 Announce Type: replace-cross Abstract: Adaptive optimization methods such as AdaGrad and Adam are widely used in modern deep neural network training, but their adaptive scaling is primarily designed fo…
- arXiv cs.AIagentsTouvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments
arXiv:2609.21828v1 Announce Type: cross Abstract: Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-language-model-based as…
- arXiv cs.AIresearchFederated Deep Clustering Networks for High-Dimensional and Heterogeneous Data
arXiv:2609.21829v1 Announce Type: cross Abstract: Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized data scenario, this…
- arXiv cs.AIagentsDo Personality-Tuned LLMs Make Better Social Agents?
arXiv:2609.21857v1 Announce Type: cross Abstract: LLMs are increasingly used in social simulations for socially interactive agents and robots, offering more flexibility than rule-based systems. However, even though they…
- arXiv cs.AIresearchNeural Cellular Automata Learn General Features in their Hidden Channels
arXiv:2609.21870v1 Announce Type: cross Abstract: Modern deep learning models achieve impressive generalization through over-parameterization, but this paradigm often struggles with overfitting and memorization in few-sh…
- arXiv cs.AIresearchBenchmarking the Explanatory Quality of Open-Weight Vision-Language Models in Face Recognition
arXiv:2609.21879v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have recently been proposed as promising tools for face recognition, as they can produce natural language explanations alongside similarity…
- arXiv cs.AIresearchDetecting Pretraining Data in Large Language Models from a Free-Energy Perspective
arXiv:2609.21888v1 Announce Type: cross Abstract: Detecting pretraining data in large language models is challenging because high likelihood can reflect either training exposure or strong generalization. In the joint spa…
- arXiv cs.AIresearchWhen Should a Failing Robot Ask? Initiating Corrective Human-Robot Dialogue from Audited Sensor Evidence
arXiv:2609.21942v1 Announce Type: cross Abstract: A robot that fails at a task faces the first decision in corrective dialogue: act on its own diagnosis, consult another onboard sensor, or interrupt a person. Choosing we…
- arXiv cs.AIresearchNemotronLabs VoiceChat: An Open Full-duplex Speech-to-Speech Model with Tool Calling Capabilities
arXiv:2609.21967v2 Announce Type: replace-cross Abstract: We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combines a streaming…
- arXiv cs.AIagentsBayesian Belief Layer for Controllable Opinion Dynamics in LLM Agents
arXiv:2609.21997v2 Announce Type: replace-cross Abstract: LLM agents in social simulation revise their opinions implicitly, in context: how open an agent is to persuasion can neither be specified nor verified, and collec…
- arXiv cs.AIresearchDiaVLo: Diagnosing Behaviours of Vision-Language Models
arXiv:2609.22008v1 Announce Type: cross Abstract: Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit desired behaviours, wh…
- arXiv cs.AIresearchGricea: An Open Science Platform for Conversational AI Research
arXiv:2609.22039v1 Announce Type: cross Abstract: We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragmented reporting of systems and study configurations h…
- arXiv cs.AIagentsValue-Sensitive Delegation in Everyday AI Agent Use: Evidence from OpenClaw
arXiv:2609.22067v1 Announce Type: cross Abstract: Users increasingly delegate work to autonomous AI agents, yet evaluations typically measure task completion rather than the values users prioritize. Using Value Sensitive…
- arXiv cs.AIresearchCollab-Solver: Collaborative Solving Policy Learning for Mixed-Integer Linear Programming
arXiv:2508.03030v3 Announce Type: replace Abstract: Mixed-integer linear programming (MILP) has been a fundamental problem in combinatorial optimization. Conventional MILP solving mainly relies on carefully designed heur…
- arXiv cs.AIresearchFact Grounded Attention: Eliminating Hallucination in Large Language Models Through Attention Level Knowledge Integration
arXiv:2509.25252v3 Announce Type: replace Abstract: "The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge." Large Language Models have conquered natural language but remain prisoners of their…
- arXiv cs.AIresearchMemeLens: Multilingual Multitask VLMs for Memes
arXiv:2601.12539v4 Announce Type: replace Abstract: Memes are a dominant medium for online communication and manipulation because meaning emerges from interactions between embedded text, imagery, and cultural context. Ex…
- arXiv cs.AIresearchBeyond Final Answers: CRYSTAL Benchmark for Transparent Multimodal Reasoning Evaluation
arXiv:2603.13099v3 Announce Type: replace Abstract: We introduce CRYSTAL (Clear Reasoning via Yielded Steps, Traceability, and Logic), a diagnostic benchmark with 6,372 instances that evaluates multimodal reasoning throu…
- arXiv cs.AIresearchTransferable knowledge graphs with executable learned operators for algorithm design
arXiv:2603.27922v2 Announce Type: replace Abstract: Procedural knowledge in algorithm design is embedded in source code and rebuilt for each new domain. We introduce Generative Executable Algorithm Knowledge Graphs (GEAK…
- arXiv cs.AIresearchBoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
arXiv:2605.09134v4 Announce Type: replace Abstract: Reinforcement learning for program repair is hindered by sparse execution feedback and coarse sequence-level rewards that obscure which edits actually fix bugs. We pres…
- arXiv cs.AIresearchOn the Limitations of Large Language Models for Conceptual Database Modeling
arXiv:2605.11986v2 Announce Type: replace Abstract: This article analyzes the use of Large Language Models (LLMs) as support for the conceptual modeling of relational databases through the automatic generation of Entity-…
- arXiv cs.AIagentsIntent-Governed Tool Authorization for AI Agents
arXiv:2606.22916v4 Announce Type: replace Abstract: Tool-using AI agents commonly operate under integration credentials whose static permissions exceed a user's current request. We present Intent-Governed Access Control…
- arXiv cs.AIagentsExplanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales
arXiv:2607.25364v3 Announce Type: replace Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection. We present Exp…
- arXiv cs.AIresearchA Forced-Structure Reduction and Verifiable Bounds for Conway's 99-Graph
arXiv:2608.11211v2 Announce Type: replace Abstract: Conway's 99-graph problem asks whether a strongly regular graph with parameters $\mathrm{srg}(99,14,1,2)$ exists. We develop two complementary lines of attack. Fixing o…
- arXiv cs.AIagentsPlanetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings
arXiv:2608.26088v3 Announce Type: replace Abstract: Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fidelity geospatial mode…
- arXiv cs.AIresearchBalance of Benchmarks: Semantic Density Reweighting for Task-Conditioned Model Comparison
arXiv:2608.30044v3 Announce Type: replace Abstract: Model comparison increasingly relies on large collections of publicly reported benchmark scores, yet common aggregation strategies trade off evidence coverage against c…
- arXiv cs.AIresearchFraglingo: Molecular Design via Attachment-Aware Autoregressive Fragment Generation
arXiv:2609.13519v2 Announce Type: replace Abstract: We introduce Fraglingo, an autoregressive molecular generator that constructs molecules step by step from chemically meaningful fragments connected through predefined a…
- arXiv cs.AIagentsMOSCOPT: Mixture-of-Skills Collective Optimization for LLM Agents
arXiv:2609.14399v2 Announce Type: replace Abstract: Natural language prompts and skills serve as the strategic backbone of LLM-based agents. Recent advances in prompt and skill optimization have achieved notable gains, y…
- arXiv cs.AIagentsRuntime Authorization for Resources Acquired by AI Agents
arXiv:2609.14744v2 Announce Type: replace Abstract: By acquiring compute, credentials, accounts, services, and other agents, autonomous AI agents can introduce new authority into a task. Payment, budget, OAuth, mandate,…
- arXiv cs.AIresearchReinforcement Learning under External Influence: Guarantees, Algorithms, and Sample Complexity
arXiv:2305.16056v5 Announce Type: replace-cross Abstract: In this paper, we study the problem of reinforcement learning under the influence of external events. For this, we consider Markov decision processes with continu…
- arXiv cs.AIresearchSoda: An Object-Oriented Functional Language for Specifying Human-Centered Problems
arXiv:2310.01961v3 Announce Type: replace-cross Abstract: We present Soda (Symbolic Objective Descriptive Analysis), a language that helps to treat qualities and quantities in a natural way and greatly simplifies the tas…
- arXiv cs.AIresearchContinuous Spiking Graph Neural Networks
arXiv:2404.01897v3 Announce Type: replace-cross Abstract: Continuous graph neural networks (CGNNs) have garnered significant attention due to their ability to generalize existing discrete graph neural networks (GNNs) by…
- arXiv cs.AIresearchUnderstanding In-context Learning of Addition via Activation Subspaces
arXiv:2505.05145v4 Announce Type: replace-cross Abstract: To perform few-shot learning, language models extract signals from a few input-label pairs, aggregate them into a learned prediction rule, and apply this rule to…
- arXiv cs.AIresearchGeneralizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions
arXiv:2509.10303v3 Announce Type: replace-cross Abstract: Online reinforcement learning (RL) approaches have demonstrated strong performance on Job Shop Scheduling (JSP) and Flexible JSP (FJSP) problems by learning sched…
- arXiv cs.AIagentsBenchmarking Autonomous Driving Planners Across Leaderboards: A Unified CARLA-Based Evaluation
arXiv:2509.22754v2 Announce Type: replace-cross Abstract: Autonomous driving remains a highly active research domain that seeks to enable vehicles to perceive dynamic environments, predict the future trajectories of traf…
- arXiv cs.AIresearchAuditing a KB Elicitation of Frontier LLM Knowledge: A Multi-dimensional Analysis of GPTKB v1.5
arXiv:2510.07024v4 Announce Type: replace-cross Abstract: LLMs are remarkable artifacts that have revolutionized a range of knowledge-intensive tasks. A significant contributor is their factual knowledge, which, to date,…
- arXiv cs.AIresearchThe Impact of Semantic Pairs on Self-Supervised Representation Learning
arXiv:2510.08722v4 Announce Type: replace-cross Abstract: Instance discrimination learns visual representations by treating different augmented views of the same image as positive pairs. While this encourages invariance…
- arXiv cs.AIresearchDeep Learning-Enhanced Real-Time Wi-Fi Sensing Through Single Transceiver Pair
arXiv:2511.02845v4 Announce Type: replace-cross Abstract: The advancement of next-generation Wi-Fi technology heavily relies on sensing capabilities, which play a pivotal role in enabling sophisticated applications. In r…
- arXiv cs.AIresearchUnderstanding Structural Representation in Foundation Models for Polymers
arXiv:2512.11881v2 Announce Type: replace-cross Abstract: From the relative scarcity of training data to the lack of standardized benchmarks, the creation of effective foundation models for polymers faces significant and…
- arXiv cs.AIresearchLarge Language Models As Shannon Lossy Compressors Not Solomonoff Induction Estimators: The Singularity Is Not Near Without Symbolic Model Synthesis
arXiv:2601.05280v5 Announce Type: replace-cross Abstract: On the one hand, the question of whether Large Language Models (LLMs) are Solomonoff induction estimators has become an explicit question at the intersection of A…
- arXiv cs.AIresearchBEAT-Net: Injecting Biomimetic Spatio-Temporal Priors for Interpretable ECG Diagnosis
arXiv:2601.07316v2 Announce Type: replace-cross Abstract: Automated electrocardiogram diagnosis using deep learning remains limited by signal-agnostic representations that treat multi-lead recordings as undifferentiated…
- arXiv cs.AIagentsHERMES: A Holistic End-to-End Risk-Aware Multimodal Embodied System with Vision-Language Models for Long-Tail Autonomous Driving
arXiv:2602.00993v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving models increasingly benefit from large vision-language models for semantic understanding, yet safe and reliable planning under long-…
- arXiv cs.AIresearchMENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs
arXiv:2602.07036v2 Announce Type: replace-cross Abstract: Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of diverse, conversati…