AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchEliteReplay: Preserving Diverse Solutions in RL Post-Training via Quality-Diversity Search
arXiv:2610.22290v1 Announce Type: new Abstract: Reinforcement learning has become a common post-training technique to improve the accuracy of LLMs on verifiable tasks. However, such training can narrow the set of solutio…
- arXiv cs.AIresearchPrivate Retrieval Augmented Generation via Random Projection
arXiv:2610.22297v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the capabilities of large language models (LLMs) by querying external structured knowledge. However, it can also introduce pri…
- arXiv cs.AIagentsA team of Gemini 4 Argon agents beats Minecraft
arXiv:2610.22319v1 Announce Type: new Abstract: We placed four Gemini 4 Argon agents in a sandboxed Minecraft survival world and gave them one goal: defeat the Ender Dragon. Each agent controlled a player via an open-sou…
- arXiv cs.AIresearchDesigning Transformers for Continuous Diffusion Language Models
arXiv:2610.22330v1 Announce Type: new Abstract: Continuous diffusion language models (CDLMs) offer an alternative approach to parallel language generation; however, most existing studies directly use transformer architec…
- arXiv cs.AIagentsKnowGPO: Knowledge-Grouped Policy Optimization for Search Agents
arXiv:2610.22331v1 Announce Type: new Abstract: Deep search agents solve knowledge-intensive tasks through long-horizon, multi-turn interactions, where assigning credit to individual search decisions is fundamentally dif…
- arXiv cs.AIresearchEvaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?
arXiv:2610.22333v1 Announce Type: new Abstract: Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiously during safety ev…
- arXiv cs.AIagentsMLExpert: Towards a Generalist Agentic Model for Autonomous Machine Learning Engineering
arXiv:2610.22344v1 Announce Type: new Abstract: Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI4A…
- arXiv cs.AIagentsFDE-Gym: The Last Mile of AI Delivery
arXiv:2610.22350v1 Announce Type: new Abstract: Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world customer delivery is diffe…
- arXiv cs.AIresearchKULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Context
arXiv:2412.07251v1 Announce Type: cross Abstract: Large language models have exhibited significant enhancements in performance across various tasks. However, the complexity of their evaluation increases as these models g…
- arXiv cs.AIresearchActive Learning of Fractional-Order Viscoelastic Model Parameters for Realistic Haptic Rendering
arXiv:2512.00667v2 Announce Type: cross Abstract: Effective medical simulators necessitate realistic haptic rendering of biological tissues that exhibit viscoelastic material properties, such as creep and stress relaxati…
- arXiv cs.AIresearchOne Is Not Enough: How People Use Multiple AI Models in Everyday Life
arXiv:2603.26107v1 Announce Type: cross Abstract: People increasingly use multiple Multimodal Large Language Models (MLLMs) concurrently, selecting each based on its perceived strengths. This cross-platform practice crea…
- arXiv cs.AIresearchBridging the Gap: Converting Read Text to Conversational Dialogue
arXiv:2605.18001v1 Announce Type: cross Abstract: In recent advancements within speech processing, converting read speech to conversational speech has gained significant attention. The primary challenge in this domain is…
- arXiv cs.AIagentsTruth for Believable AI: Expressed Doubt, Provenance, and Belief Revision as an Engineerable Stance
arXiv:2609.26035v1 Announce Type: cross Abstract: Conversational agents often express answers in a uniformly confident register. We test whether expressed uncertainty, provenance-aware assertion, and explicit belief revi…
- arXiv cs.AIagentsRICE-Alpha: Reliability-Informed Correction with Event Graphs for LLM-Agent Stock Forecasting
arXiv:2609.34004v2 Announce Type: cross Abstract: Equity-relevant news evolves through temporally dependent corporate events, making historical information useful only when event continuity, information availability, and…
- arXiv cs.AIresearchReal-time Chatbot Romance Scam Detection in Stage Classification
arXiv:2610.20631v1 Announce Type: cross Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the study, a chatbot has dev…
- arXiv cs.AIresearchExploring the Design Space of Permutation Diffusion LLMs
arXiv:2610.20635v1 Announce Type: cross Abstract: Permutation generation with language models requires both text-conditioned ranking and a global one-to-one assignment between candidates and output positions. We study th…
- arXiv cs.AIresearchCoTS: Competitive Token Selection for Latent Reasoning in Large Language Models
arXiv:2610.20642v1 Announce Type: cross Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden states, enabling richer…
- arXiv cs.AIresearchOpen Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans
arXiv:2610.20690v1 Announce Type: cross Abstract: The present work is concerned with how to measure, at scale, the multi-dimensional impact of generative AI models on the individuals who use them. In service of this goal…
- arXiv cs.AIresearchWorldCast: Exploring Intelligent Visual Generation in World State Prediction
arXiv:2610.20731v2 Announce Type: replace-cross Abstract: Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar capabilities…
- arXiv cs.AIresearchInterpreting Language Model Parameters
arXiv:2610.20748v1 Announce Type: cross Abstract: Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previous work has uncovere…
- arXiv cs.AIresearchOptimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets
arXiv:2610.20753v1 Announce Type: cross Abstract: Large language models (LLMs) trained on vast amounts of data have demonstrated impressive performance over a range of tasks, but future performance gains will require inc…
- arXiv cs.AIresearchReference-Guided Turn-Taking Style Transfer for Full-Duplex Spoken Language Models
arXiv:2610.20763v1 Announce Type: cross Abstract: Full-duplex spoken language models decide at every frame whether to take the floor, defining a conversational personality -- yet each set of weights encodes exactly one,…
- arXiv cs.AIagentsINFUSE: A Unified Surface Benchmark for Indirect Prompt Injection in Agentic Systems
arXiv:2610.20776v1 Announce Type: cross Abstract: LLM-based agents increasingly execute long-horizon, end-to-end workflows involving shell commands, code modification, dependency installation, and interaction with remote…
- arXiv cs.AIresearchVerdict: Encode Once, Decide Many
arXiv:2610.20778v1 Announce Type: cross Abstract: Automating organizational work means answering many small typed questions about one piece of state (does this email need a reply, how urgent is it, who owns it) with prob…
- arXiv cs.AIresearchReasonUni: Reasoning-Augmented Reconstruction Advances Unified Multimodal Models
arXiv:2610.20781v1 Announce Type: cross Abstract: Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs). Reconstructive post-training couples these tasks,…
- arXiv cs.AIresearchWolof-Adapted Industry-Ready Open-Weight Language Models
arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance, and sovereignty co…
- arXiv cs.AIresearchCoTranslator: Reverse to Forward Chain-of-Thought Translator for Reasoning Distillation
arXiv:2610.20828v1 Announce Type: cross Abstract: Reasoning distillation requires chain-of-thought (CoT) data with correct answers, but obtaining such data efficiently remains challenging. Forward CoT generation (FCG) fo…
- arXiv cs.AIresearchAmortizing Sequential Experimental Design in Reasoning LLMs
arXiv:2610.20832v1 Announce Type: cross Abstract: Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather information in experimental de…
- arXiv cs.AIresearchProbing Negation Understanding in Vision-Language Models With Object Attention
arXiv:2610.20852v1 Announce Type: cross Abstract: Negation is a fundamental aspect of language understanding and it is important vision-language models (VLMs) are able to process it effectively. We investigate how VLMs p…
- arXiv cs.AIagentsSHRED: Self-Play for Heterogeneous Road-Users without Expert Demonstrations
arXiv:2610.20866v1 Announce Type: cross Abstract: Realistic traffic simulation and autonomous planning both depend on modeling interactions among heterogeneous road users whose dynamics, constraints, and behaviors differ…
- arXiv cs.AIresearchWrong Votes, Right Gradients: Why Majority-Vote Rewards Track Verifiable RL
arXiv:2610.20898v1 Announce Type: cross Abstract: Reinforcement learning with self-generated labels, such as majority vote over a model's own samples, often recovers most of the gain of training with verifiable rewards.…
- arXiv cs.AIresearchTGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping
arXiv:2610.20901v1 Announce Type: cross Abstract: Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation. Given the task of using a knife to "slice bread," a robot must choose…
- arXiv cs.AIresearchReplicable Dueling Bandits
arXiv:2610.20908v1 Announce Type: cross Abstract: Dueling bandits choose each comparison based on earlier noisy outcomes, so two runs on the same preferences can compare different pairs. We study replicable dueling bandi…
- arXiv cs.AIresearchForecast lead time and the timing of crew deployment for weather-driven power outages using AI weather models
arXiv:2610.20918v1 Announce Type: cross Abstract: Utilities request mutual aid crews to restore power after severe storms, and requesting early secures more crews but relies on less accurate forecasts. We examined how fo…
- arXiv cs.AIagentsScrewtape: Adversarial Transcript Editing for Monitor Red-Teaming
arXiv:2610.20941v1 Announce Type: cross Abstract: We present Screwtape, a pipeline that converts real agent transcripts into attacks that evade action-only monitors. An LLM attacker edits a transcript so that the agent c…
- arXiv cs.AIagentsSame Context, Different Agents: A Behavioral Study of Semantic Layers, Multi-Agent Orchestration and Memory Compaction in Data Agents
arXiv:2610.20959v2 Announce Type: replace-cross Abstract: Answering questions over heterogeneous data means combining evidence from files, databases, documents and the web. Data agents automate this, but their success de…
- arXiv cs.AIresearchSOMA: Stack-of-Objects Manipulation using a Quadruped Robot
arXiv:2610.20968v1 Announce Type: cross Abstract: Executing heavy-duty physical manipulation in unpredictable environments remains a major challenge for quadrupedal robots lacking dedicated manipulators. This paper prese…
- arXiv cs.AIresearchHow to Train Your Little Dragon: Teaching a Small Language Model to Construct and Refine GPU Optimization Scripts
arXiv:2610.20980v1 Announce Type: cross Abstract: Compiler transformations interact, making GPU kernel optimization a search for combinations that preserve the computation while improving performance. We introduce HOW TO…
- arXiv cs.AIresearchEigDiff: Eigensample Diffusion - or how to significantly reduce training dataset size with marginal performance variation?
arXiv:2610.20999v1 Announce Type: cross Abstract: Diffusion models are notoriously expensive to train, requiring large-scale datasets to learn how to gradually reverse the noise from images over multiple small denoising…
- arXiv cs.AIresearchLearning to Read Out: Unembedding Dynamics in Language Model Pretraining
arXiv:2610.21025v1 Announce Type: cross Abstract: When does a language model acquire a capability? Developmental studies usually answer this by tracking when models start producing the correct token. But that prediction…
- arXiv cs.AIagentsSCARCE: Emergent Institutions in Long-Horizon Multi-Agent Coding Systems
arXiv:2610.21029v2 Announce Type: replace-cross Abstract: As autonomous agents become widely deployed, coordinating access to shared computing resources and services will become increasingly important. Recent incidents h…
- arXiv cs.AIagentsReviewPilot: A Multi-Agent System for Screening and Data Extraction in Systematic Reviews
arXiv:2610.21042v1 Announce Type: cross Abstract: Systematic literature reviews follow the PRISMA process of screening scholarly works and extracting evidence from included studies. Deep research tools based on large lan…
- arXiv cs.AIresearchPremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews
arXiv:2610.21046v1 Announce Type: cross Abstract: Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate what a paper says. We introduce ReviewFact, a benchma…
- arXiv cs.AIresearchBellman-Consistent Trajectory RL for LLM Arithmetic Reasoning
arXiv:2610.21060v1 Announce Type: cross Abstract: To address sparse terminal rewards in LLM arithmetic reasoning, we propose a Bellman-consistent trajectory RL method. Our framework introduces Trajectory Bellman Residual…
- arXiv cs.AIagentsApprove What, Exactly? Effect Binding and Trusted Rendering for Agent Step-Up Authorization
arXiv:2610.21063v1 Announce Type: cross Abstract: AI agents now pause for approval before they send money, delete files or email outsiders, and that approval is usually treated as a second factor. We argue it is one only…
- arXiv cs.AIresearchA Jury, Not an Electorate: Label-Free Reliability Estimation for Ensembles of Language Models
arXiv:2610.21085v2 Announce Type: replace-cross Abstract: An ensemble of language models is a jury, not an electorate. The answers are testimony from witnesses of unknown reliability, and the question is not what the maj…
- arXiv cs.AIresearchSIEVE: Overcoming Topological Obstruction in Equivariant Self-Supervised Learning
arXiv:2610.21087v1 Announce Type: cross Abstract: We identify a theoretical incompatibility between 3D point cloud masked autoencoding and SE(3)-equivariant networks. We prove that standard masking triggers a topological…
- arXiv cs.AIagentsToolBottleneckBench: Measuring Tool-Agent Performance under Controlled Pressures and Fixed Harness Budgets
arXiv:2610.21098v1 Announce Type: cross Abstract: The success score of a tool agent reflects both its model and the budgets of the harness that runs it. We present ToolBottleneckBench, a benchmark that measures tool-agen…
- arXiv cs.AIagentsSSR: Structural Signal Retriever for Scalable Agent Discovery in LLM-Orchestrated Multi-Agent Systems
arXiv:2610.21113v1 Announce Type: cross Abstract: Large-scale multi-agent ecosystems require mechanisms for discovering suitable agents without exposing entire registries to a large language model (LLM) orchestrator. The…
- arXiv cs.AIresearchDST-Net: Decomposed Spatio-Temporal Network for Time Series Forecasting
arXiv:2610.21123v1 Announce Type: cross Abstract: Series decomposition has emerged as a widely acknowledged paradigm in deep time series forecasting models. However, existing approaches predominantly employ a homogeneous…