AI news archive.
19,885 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsLLM-as-an-Investigator: Evidence-First Agentic Reasoning for Robust Interactive Problem Diagnosis
arXiv:2606.13220v2 Announce Type: replace Abstract: Large language models (LLMs) are used for technical troubleshooting, where problem descriptions are often incomplete and multiple causes can explain the same symptoms.…
- arXiv cs.AIagentsMulti-Agent Transactive Memory
arXiv:2606.19911v2 Announce Type: replace Abstract: Decentralized deployment of LLM agents with diverse capabilities motivates infrastructure for knowledge sharing across heterogeneous agent populations. Just as search e…
- arXiv cs.AIresearchAI Alignment From Social Choice Perspectives
arXiv:2606.21550v2 Announce Type: replace Abstract: Alignment from human feedback uses human judgments about model outputs to steer the behavior of language models after pretraining. When those judgments reflect conflict…
- arXiv cs.AIresearchMind the Delay: Latency-aware Query Routing for Heterogeneous LLM pools
arXiv:2607.18253v2 Announce Type: replace Abstract: Large language model (LLM) query routers typically assign each query to a suitable model that balances response accuracy and monetary cost. Subsequently, separate syste…
- arXiv cs.AIresearchAI and Consumer Rights in India Working Paper
arXiv:2608.12863v2 Announce Type: replace Abstract: As AI systems proliferate in consumer facing applications, questions about liability for AI related harms remain unresolved. This working paper examines whether India's…
- arXiv cs.AIresearchWhen Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning
arXiv:2608.14610v2 Announce Type: replace Abstract: Legal reasoning requires identifying which version of a statute applies to a case, typically based on when the legally relevant events occurred rather than when the cas…
- arXiv cs.AIagentsAgent Gym: A Framework for Continuous Evaluation and Evolution of LLM Agents Through Human-in-the-Loop Feedback
arXiv:2608.15591v2 Announce Type: replace Abstract: Large Language Model (LLM) agents deployed in production environments face a fundamental tension: the agent's behavior is frozen at deployment time, while the business…
- arXiv cs.AIagentsMegaMem: A Retrieval Solution for Ultra-Large Context Windows
arXiv:2608.22137v2 Announce Type: replace Abstract: Modern language models and agents increasingly require persistent memory for complete codebases, long interaction histories, and heterogeneous enterprise records. The k…
- arXiv cs.AIresearchMEMONDEMAND: A Memory Management System for Large-Scale Enterprise Data
arXiv:2608.22141v2 Announce Type: replace Abstract: Enterprise repositories are large, heteroge- neous, and continuously updated, making re- trieval difficult when efficient access, source- faithful evidence, and cross-q…
- arXiv cs.AIresearchDesign the Feedback, Not Just the Reward: Environments for Open-Ended Reinforcement Learning
arXiv:2608.27906v4 Announce Type: replace Abstract: Reinforcement learning has advanced large language models on tasks with reliable verifiers, where checking an outcome provides a clear basis for reward. Extending this…
- arXiv cs.AIresearchBLOOM-WILT: Logit Tilting for Behaviour Elicitation in Automated LLM Auditing
arXiv:2608.31105v2 Announce Type: replace Abstract: Users of a deployed language model routinely encounter behaviours that have never been observed during testing, since deployment puts the model through orders of magnit…
- arXiv cs.AIresearchTask-Level Natural Language Priors as Learning Signals for Low-Resource LLM Training
arXiv:2609.02244v2 Announce Type: replace Abstract: Large language models (LLMs) often struggle when low-resource training data are ambiguous or incomplete. Task-level natural-language priors can provide useful guidance…
- arXiv cs.AIagentsConstructing and Evaluating Clinical Reasoning Trajectories for Medical Agent
arXiv:2609.05090v2 Announce Type: replace Abstract: Evaluation of medical artificial intelligence agents remains predominantly answer-centric, assessing only the correctness of final outputs while overlooking the quality…
- arXiv cs.AIagentsCABAL: Multi-Agent Simulacra for Tracing the Effects of Collusive Bidding in Peer Review
arXiv:2609.05227v3 Announce Type: replace Abstract: Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats bidding, reviewe…
- arXiv cs.AIagentsFrom Simulated Citizens to Simulated Deliberation: Challenges in Representation and Interaction
arXiv:2609.07573v2 Announce Type: replace Abstract: Can LLM agents simulate how a real public would deliberate? For such simulations to be meaningful, agents must reflect the population's opinions, and their views must b…
- arXiv cs.AIresearchT-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts
arXiv:2609.12286v2 Announce Type: replace Abstract: Introducing large language models (LLMs) into evolutionary computation enables semantic generation of candidates, but the classical problem of maintaining population di…
- arXiv cs.AIresearchDistributionally Robust Regularization of Sparse Integer Programming Trained Learning Models
arXiv:2311.01994v2 Announce Type: replace-cross Abstract: Building explainable machine learning models is crucial for human users to be able to interpret the proposed statistical relationship obtained from the training d…
- arXiv cs.AIresearchInkSight: Offline-to-Online Handwriting Conversion by Teaching Vision-Language Models to Read and Write
arXiv:2402.05804v5 Announce Type: replace-cross Abstract: Digital note-taking is gaining popularity, offering a durable, editable, and easily indexable way of storing notes in a vectorized form, known as digital ink. How…
- arXiv cs.AIresearchPairwise Difference Learning for Classification
arXiv:2406.20031v2 Announce Type: replace-cross Abstract: Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping from instances to o…
- arXiv cs.AIresearchLLMR: Knowledge Distillation with a Large Language Model-Induced Reward
arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) tasks. However, these…
- arXiv cs.AIresearchSTAMP: Symmetric Temporal Averaging Message Passing for Domain Adaptation in Chronologically Split Graphs
arXiv:2411.10957v2 Announce Type: replace-cross Abstract: This paper addresses domain adaptation in graph-structured data under chronological splits. We consider transductive semi-supervised node classification (SSNC), i…
- arXiv cs.AIresearchA self-learning framework for adaptive free-form pipe routing in aeroengines
arXiv:2504.03669v2 Announce Type: replace-cross Abstract: Pipe routing is a highly complex, time-consuming, and no-deterministic polynomial-time hard (NP-hard) problem in aeroengine design. Despite extensive research eff…
- arXiv cs.AIresearchTowards Reliable Long-Context Reasoning: Detecting Unanswerable Questions via FactGuard
arXiv:2504.05607v2 Announce Type: replace-cross Abstract: Despite the success of Large Language Models (LLMs) in long-context tasks, their reliability in recognizing unanswerable questions remains a critical challenge. I…
- arXiv cs.AIresearchPanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolution
arXiv:2507.09227v2 Announce Type: replace-cross Abstract: Interest in generating realistic synthetic medical images has grown in recent years. Such datasets can mitigate the scarcity of public data for artificial intelli…
- arXiv cs.AIresearchAdaptive Duration Model for Text Speech Alignment
arXiv:2507.22612v3 Announce Type: replace-cross Abstract: Speech-to-text alignment is a critical component of neural text to speech (TTS) models. Autoregressive TTS models typically use an attention mechanism to learn th…
- arXiv cs.AIagentsAI Scientists for Building Virtual-Cell Models
arXiv:2508.02276v3 Announce Type: replace-cross Abstract: Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hypotheses. Whether th…
- arXiv cs.AIresearchUniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrieval
arXiv:2508.04136v4 Announce Type: replace-cross Abstract: Few-shot fine-grained visual classification (FGVC) aims to discriminate between subtly different categories with very limited data. While Multimodal Large Languag…
- arXiv cs.AIagentsDrive As You Like: Multi-Head Diffusion with Reinforcement Learning for Personalized Driving
arXiv:2508.16947v3 Announce Type: replace-cross Abstract: Personalized autonomous driving requires understanding the driving needs implicit in user requests. This is challenging when driving demonstrations lack style ann…
- arXiv cs.AIresearchChronoberg: A 250-Year Diachronic Corpus with Temporal Affective Lexicons for Language Model Analysis
arXiv:2509.22360v3 Announce Type: replace-cross Abstract: Large language models (LLMs) excel at operating at scale by leveraging social media and data crawled from the web. Whereas existing corpora are diverse, their fre…
- arXiv cs.AIresearchUncovering Grounding IDs: How External Cues Shape Multi-Modal Binding
arXiv:2509.24072v5 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) perform well on multimodal tasks, but their ability to reason and precisely align visual and textual information still has ro…
- arXiv cs.AIresearchMulti-task Neural Diffusion Processes
arXiv:2510.03419v3 Announce Type: replace-cross Abstract: Neural diffusion processes provide a scalable, non-Gaussian approach to modelling distributions over functions, but existing formulations are limited to single-ta…
- arXiv cs.AIresearchRAG4Tickets: AI-Powered Ticket Resolution via Retrieval-Augmented Generation on JIRA and GitHub Data
arXiv:2510.08667v3 Announce Type: replace-cross Abstract: Modern software teams frequently encounter delays in resolving recurring or related issues due to fragmented knowledge scattered across JIRA tickets, developer di…
- arXiv cs.AIresearchScientific feedback reveals productive regimes beyond training conventions
arXiv:2512.15756v2 Announce Type: replace-cross Abstract: Human-imposed design conventions can restrict the alternatives represented in scientific training data and shape the search preferences learned by generative mode…
- arXiv cs.AIresearchBenchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration
arXiv:2512.20159v2 Announce Type: replace-cross Abstract: Code from LLM-assisted development may contain defects like API hallucinations, motivating the development of code evaluation metrics to assess such code before d…
- arXiv cs.AIresearchContextual Probability and Operational Minimality in Tug-of-War Decision Making
arXiv:2601.10034v4 Announce Type: replace-cross Abstract: What connects minimal decision-making to contextual probability? We address this question through the Tug-of-War (TOW) principle, a resource-coupled mechanism for…
- arXiv cs.AIresearchVDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents
arXiv:2602.00122v5 Announce Type: replace-cross Abstract: Image editing models can modify visual content through natural language, but editing dense documents requires precise local changes amid tightly coupled text, tab…
- arXiv cs.AIresearchProduct Interaction: An Algebraic Formalism for Deep Learning Architectures
arXiv:2602.02573v2 Announce Type: replace-cross Abstract: Modern neural architectures are largely developed as distinct empirical constructions, despite recurring principles across convolutional, attention, state-space,…
- arXiv cs.AIresearchLanguage Models Struggle to Use Representations Learned In-Context
arXiv:2602.04212v3 Announce Type: replace-cross Abstract: Though large language models (LLMs) have enabled great success across a wide variety of tasks, they still appear to fall short of one of the loftier goals of arti…
- arXiv cs.AIresearchReText: Text Boosts Generalization in Image-Based Person Re-identification
arXiv:2602.05785v2 Announce Type: replace-cross Abstract: Generalizable image-based person re-identification (Re-ID) aims to recognize individuals across cameras in unseen domains without retraining. While visual feature…
- arXiv cs.AIagentsOrchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation
arXiv:2602.18891v2 Announce Type: replace-cross Abstract: Advances in large language models (LLMs) are rapidly transforming scientific work, yet empirical evidence on how these systems reshape research activities remains…
- arXiv cs.AIresearchRMBench: Memory-Dependent Robotic Manipulation Benchmark with Insights into Policy Design
arXiv:2603.01229v4 Announce Type: replace-cross Abstract: Robotic manipulation policies have made rapid progress in recent years, yet most existing approaches give limited consideration to memory capabilities. Consequent…
- arXiv cs.AIresearchLearning Not To Interfere: Adapting Experts For Model Merging
arXiv:2603.13467v2 Announce Type: replace-cross Abstract: Model merging has shown that multitask models can be created by directly combining the parameters of different models that are each specialized on tasks of intere…
- arXiv cs.AIresearchFrom Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Coding
arXiv:2603.15270v3 Announce Type: replace-cross Abstract: Medical coding, which assigns standardized ICD codes to clinical documents, is a fundamental yet challenging task in modern healthcare. It requires extensive know…
- arXiv cs.AIresearchWhat Tracks Hard-Negative Transfer? A Study of Lexical and Semantic Signals
arXiv:2603.20990v5 Announce Type: replace-cross Abstract: Which properties of hard-negative supervision track dense-retriever transfer before training? We compare lexical noncoverage, frozenencoder similarity statistics,…
- arXiv cs.AIresearchInverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting
arXiv:2603.23463v3 Announce Type: replace-cross Abstract: Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-to-image models offe…
- arXiv cs.AIresearchTensorDex: A Compact, Tensor-Centric Storage System for Modern AI Models
arXiv:2604.17104v3 Announce Type: replace-cross Abstract: Modern model hubs store hundreds of petabytes of large language models (LLMs), with fine-tuned variants dominating the storage footprint. These variants contain s…
- arXiv cs.AIresearchEmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training
arXiv:2604.20012v2 Announce Type: replace-cross Abstract: Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from off-the-she…
- arXiv cs.AIresearchOn the Privacy of LLMs: An Ablation Study
arXiv:2605.02255v2 Announce Type: replace-cross Abstract: Large language models (LLMs) face diverse privacy threats, yet existing studies typically evaluate individual attacks in isolation, offering limited guidance on w…
- arXiv cs.AIresearchCRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning
arXiv:2605.05732v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can learn new tasks through fine-tuning, but learning tasks sequentially often leads to catastrophic forgetting of earlier ones. This…
- arXiv cs.AIagentsPlan Before You Trade: Inference-Time Optimization for RL Trading Agents
arXiv:2605.12653v2 Announce Type: replace-cross Abstract: Reinforcement learning agents for portfolio management are typically trained and deployed as static policies, with no mechanism for policy adjustments using price…