AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAgent Memory with Episodic Retrieval for Financial Decision-Making
arXiv:2609.28771v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in financial analysis and reasoning, inspiring recent advances in agent-based trading frameworks. While t…
- arXiv cs.AIresearchLearned Cross-Task Relationships in Multi-Task Models
arXiv:2609.28776v2 Announce Type: replace Abstract: We propose a framework that learns cross-task relationships in multi-task models by approximating the joint distribution of task labels through targeted pairwise relati…
- arXiv cs.AIagentsRECLAIM: Can Agents Reproduce the Claims of Machine Learning Papers?
arXiv:2609.28850v1 Announce Type: new Abstract: Reproducing a machine learning paper involves most research steps, from installing software and debugging to running experiments, work that AI agents increasingly do. We in…
- arXiv cs.AIresearchHuman-AI-Powered Hypothesis Testing: Cost-Aware Selective AI Scoring and Sequential Human Escalation
arXiv:2609.28859v1 Announce Type: new Abstract: Large language models are increasingly used as inexpensive judges to evaluate outputs, label data, and assess whether a system meets a desired quality standard. Yet using A…
- arXiv cs.AIagentsForecast-Dojo: Replayable Environments for Benchmarking and Training LLM Forecasting Agents
arXiv:2609.28876v2 Announce Type: replace Abstract: Forecasting requires large language model (LLM) agents to gather evolving evidence, revise their beliefs, and make calibrated predictions over time. Yet evaluating and…
- arXiv cs.AIagentsHarness Tokenomics: A Router for the Enterprise Agentic Control Plane
arXiv:2609.28919v2 Announce Type: replace Abstract: Harnesses, the products that run AI coding agents, are multiplying, and enterprises are rolling them out to their employees. What started as pilots with a few hundred s…
- arXiv cs.AIresearchPFArena: Benchmarking Language Models for Protein Modification
arXiv:2609.28921v1 Announce Type: new Abstract: Protein modification requires navigating an immense sequence space, yet wet-lab validation remains low-throughput and costly. Although computational paradigms including pro…
- arXiv cs.AIresearchFrom Static Personal Values to Contextualized Personalization: Bayesian Personalized Value Alignment for LLMs
arXiv:2609.28942v1 Announce Type: new Abstract: Personalized value alignment has become increasingly important as large language models (LLMs) are expected to accommodate diverse user preferences. However, existing metho…
- arXiv cs.AIagentsBack to the Definition: Estimating Step-Level Advantages via Trajectory Graphs for Agentic Reinforcement Learning
arXiv:2609.28963v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) methods, such as GRPO and its variants, have become a leading paradigm for training reasoning and agentic large language models (LLM…
- arXiv cs.AIagentsWhen Does Action Credit Need Updating?
arXiv:2609.29007v1 Announce Type: new Abstract: Tool-using agents are continually updated with new interaction data. After each policy update, however, previously estimated action credits may become stale. Recomputing th…
- arXiv cs.AIagentsAlphaDiverse: Post-Training Local Quantitative Research Agents for Diverse Exploration in Alpha Factor Mining
arXiv:2609.29014v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems can automate alpha factor mining, but their reliance on external APIs limits control over cost, availability, and confi…
- arXiv cs.AIagentsMeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks
arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality persistently degrades.…
- arXiv cs.AIagentsSLCA-GRPO: Resolving Cross-Segment Credit Misattribution in Tool-Calling RL
arXiv:2609.29050v1 Announce Type: new Abstract: Tool-calling agents produce heterogeneous outputs, interleaving structured tool invocations with user-facing natural language summaries. This output heterogeneity presents…
- arXiv cs.AIagentsFrom Self-Distillation to Self-Practice: Privileged Information for Multi-Turn Agents
arXiv:2609.29051v2 Announce Type: replace Abstract: On-policy self-distillation (OPSD) has become a popular recipe for post-training LLM agents. It supervises the agent model at the token level with a stronger teacher vi…
- arXiv cs.AIresearchCRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars
arXiv:2609.29075v1 Announce Type: new Abstract: Cancer registrars, including Oncology Data Specialists (ODSs), must interpret complex and frequently updated coding and staging standards. We developed CRISS (Cancer Regist…
- arXiv cs.AIresearchA Rapid Pipeline for Training and Deploying ML Models on WeBe Band
arXiv:2609.29084v1 Announce Type: new Abstract: Developing optimized machine-learning algorithms for edge devices with limited computational and memory resources is challenging, time-consuming, and highly dependent on de…
- arXiv cs.AIresearchFunctional Architecture of European Electricity Trading Markets: Requirements for AI Supported Trading Systems under Regulatory Constraints
arXiv:2609.29108v2 Announce Type: replace Abstract: European electricity trading in the EU operates as a constrained multi-layer system in which legal design, exchange microstructure, and network physics are executed joi…
- arXiv cs.AIresearchCounterRoute: Self-Routed Reasoning via Hierarchical Counterfactual Credit Assignment
arXiv:2609.29109v2 Announce Type: replace Abstract: Reasoning-capable language models often produce long chains of thought when direct answers suffice, wasting inference compute. Dual-mode models offer both thinking and…
- arXiv cs.AIresearchSharp Limits for Honest Uncertainty in Hard-Budget Repeated Evaluation
arXiv:2609.29140v1 Announce Type: new Abstract: Repeated evaluation can estimate a benchmark score accurately while still requiring replication to certify narrow uncertainty. We characterize that requirement on a fixed g…
- arXiv cs.AIagentsScope Before You Persist: Preventing Cross-Family Interference in Agent Memory
arXiv:2609.29144v1 Announce Type: new Abstract: Persistent memory lets language-model agents improve prompts and skills without updating model weights. We show that matching retrieval scope to certification scope enables…
- arXiv cs.AIresearchClaim-Gated Source-Risk Auditing for Generative Search
arXiv:2609.29145v2 Announce Type: replace Abstract: A generative search answer can cite a supported passage yet omit a source relationship that changes its interpretation. We specify a claim-gated audit of the query-sour…
- arXiv cs.AIagentsA Wrong Turn Does Not Ruin the Journey: Deviation-Guided Skill Self-Evolution for LLM Agents
arXiv:2609.29154v1 Announce Type: new Abstract: Large language model agents increasingly rely on natural-language skills to solve complex tool-use tasks. However, such tasks often admit multiple valid solution paths, mak…
- arXiv cs.AIagentsIndicBankBench: Evaluating Safety and Reliability of Language Model Assistants in Indian Retail Banking
arXiv:2609.29167v1 Announce Type: new Abstract: Banking assistants must use account-specific information to answer requests and, in many cases, take actions through tools. Evaluating only the final response misses import…
- arXiv cs.AIresearchRight Choice of Classification Algorithms Based on Reinforcement Learning for Prediction of Non-Alcoholic Fatty Liver
arXiv:2609.29181v1 Announce Type: new Abstract: There are many complex issues in the world of artificial intelligence. Some of these problems are solved using other artificial intelligence methods, which are called artif…
- arXiv cs.AIresearchThe Entropy Triangle Method (ETM): A novel framework for the prevention of cardiac arrhythmia with a review of more than 10,000 patients
arXiv:2609.29187v1 Announce Type: new Abstract: One of the most important problems in medicine is to facilitate prediction. In this study, we propose entropy triangle method, a novel framework for predicting heart rhythm…
- arXiv cs.AIagentsWhen Honesty is Not Enough in AI Debate
arXiv:2609.29189v1 Announce Type: new Abstract: Scalable oversight aims to verify the behaviour of agents whose capabilities exceed those of their overseers. AI debate has been proposed as an oversight solution in which…
- arXiv cs.AIagentsASIRF: An Agentic Framework for Context-Dependent Sensitive Information Redaction
arXiv:2609.29191v1 Announce Type: new Abstract: Sensitive information is defined by domain and intent, not a universal category, yet redaction systems such as privacy filters and named-entity recognizers fix a taxonomy a…
- arXiv cs.AIagentsTowards An LLM-Driven Unified Conversion Framework for BT and FSM in Autonomous Intelligent Systems
arXiv:2609.29228v1 Announce Type: new Abstract: Finite state machine (FSM) and behavior trees (BT) are widely adopted behavioral modeling paradigms for autonomous intelligent systems. While functionally equivalent and in…
- arXiv cs.AIagentsPolicy as Code: A Coroutine-Bridge Harness for Fast-Reasoning Reliability on CAR-bench
arXiv:2609.29251v1 Announce Type: new Abstract: CAR-bench evaluates whether tool-using agents stay reliable under real-world uncertainty, executing every tool inside the evaluator so that each tool-result exchange is a s…
- arXiv cs.AIresearchBaszta: Data-Centric Fine-Tuning of a Polish Multi-Label Safety Classifier
arXiv:2609.29266v1 Announce Type: new Abstract: We develop a multi-label Polish content-safety classifier by fine-tuning allegro/herbert-base-cased (124M) across five categories (hate, vulgarity, sexual content, crime, s…
- arXiv cs.AIresearchALOE: Semantically Addressed Low-Rank Operators for Knowledge Editing
arXiv:2609.29269v1 Announce Type: new Abstract: Knowledge editing changes what a model knows by modifying parameters so that a requested fact updates while unrelated behavior is preserved. This is usually treated as a wr…
- arXiv cs.AIresearchFrom Text Decisions to Pixels: An Study of Jev-Style Visual Choice Model
arXiv:2609.29283v1 Announce Type: new Abstract: Visual software often needs a decision over supplied alternatives rather than a generated explanation. We present PixelJev, a native-image decision interface that maps an i…
- arXiv cs.AIresearchWhen No One Owns the Judgment: Accountability Under Contribution Dissolution in Human-AI Collaboration
arXiv:2609.29312v2 Announce Type: replace Abstract: Communities often respond to potentially AI-assisted work by asking three questions: Was AI used? Was that use disclosed? Can hidden use be detected? These questions pl…
- arXiv cs.AIagentsSkinAgent AI: A Safety-Grounded Multimodal Agentic Framework for Non-Diagnostic Skincare Support
arXiv:2609.29341v1 Announce Type: new Abstract: Consumer-facing skincare AI must coordinate visual evidence, product information, tool use, and user-facing actions within explicit evidence and safety boundaries. This stu…
- arXiv cs.AIresearchThe Last Human Gate: Forward Deployed Engineering for Governance Automation
arXiv:2609.29345v1 Announce Type: new Abstract: Enterprise governance requires decisions, evidence, and accountable authority; it does not require every review task to retain its current human implementation. We develop…
- arXiv cs.AIresearchBeyond Simple Input-Output Assessment Tasks: Leveraging Automated Programming Assessment for Non-Trivial Courses
arXiv:2609.29363v1 Announce Type: new Abstract: The public visibility of Artificial Intelligence (AI) is growing rapidly, driven by the positive impact of its applications across diverse fields of knowledge. In this new…
- arXiv cs.AIagentsEpistemic-Probabilistic Model for Guarded Multi-Agent LLM Coordination
arXiv:2609.29366v1 Announce Type: new Abstract: Multi-agent large language models (LLMs) have become ubiquitous in applied AI, yet their theoretical foundations remain surprisingly understudied. Viewed through the lens o…
- arXiv cs.AIresearchAn auditable conditional-strategy framework for open-ended decision-making in complex lung cancer
arXiv:2609.29381v2 Announce Type: replace Abstract: Complex lung cancer decisions can involve several defensible pathways whose eligibility, sequencing and safety depend on unresolved information. Effective support must…
- arXiv cs.AIresearchWearable ECG Quality Assessment: A Deep Learning and Ambulatory Context-Awareness Approach
arXiv:2609.29396v1 Announce Type: new Abstract: This paper presents and evaluates a Deep Learning-based (DL-based) Signal Quality Assessment (SQA) model to distinguish between clean and noisy ambulatory Electrocardiogram…
- arXiv cs.AIresearchRD-JEPA: Predictive latent pretraining for few-trajectory transfer across reaction--diffusion equations
arXiv:2609.29403v1 Announce Type: new Abstract: Learning surrogates for time-dependent partial differential equations often requires a new simulation corpus when the governing operator changes. We introduce RD-JEPA, a jo…
- arXiv cs.AIresearchJust Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures
arXiv:2609.29429v1 Announce Type: new Abstract: Detectors of alignment failures screen deployed language models and score alignment benchmarks. Most are generative judges that spend a decoding pass on every criterion, an…
- arXiv cs.AIagentsSWE-Prometheus: Measuring Engineering Governance Improvements in Real-World Repositories
arXiv:2609.29465v3 Announce Type: replace Abstract: Large language model based coding agents have made substantial progress on repository-level software engineering tasks. Existing repository benchmarks, however, usually…
- arXiv cs.AIagentsEvaluation of Multi-Turn Consistency in LLM Agents: Survival Analysis and Failure-Rationale Taxonomy
arXiv:2609.29508v1 Announce Type: new Abstract: Large language model (LLM) agents may perform well on isolated tasks yet drift into inconsistency over extended interaction. We evaluate temporal consistency in a controlle…
- arXiv cs.AIagentsDelay-of-Gratification as a Multi-Agent Survival Micro-benchmark for Long-Horizon LLMs: Social Exposure, Personas, and Tool Use Budgets
arXiv:2609.29509v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as multi-turn agents that must sustain goals, use tools, and adapt to other agents over extended interactions. Howeve…
- arXiv cs.AIresearchBiGraph-Diffuse: A Bidirectional Diffusion Language Model with Graph-Structured Retrieval For Mental Health Counseling
arXiv:2609.29519v1 Announce Type: new Abstract: Mental health disorders affect hundreds of millions of people around the world, yet access to professional counseling remains severely limited. AI-powered dialogue systems…
- arXiv cs.AIagentsStale Does Not Mean Unsafe: Guard Precision for Tool-Using LLM Agents under Infrastructure State Races
arXiv:2609.29522v1 Announce Type: new Abstract: Tool-using language-model agents increasingly mutate schedulers, data pipelines, object stores, and access-control systems. Between an agent's read and its commit, external…
- arXiv cs.AIresearchClinical Knowledge Graphs for Chest X-Ray Device Reasoning
arXiv:2609.29536v1 Announce Type: new Abstract: Chest radiographs are routinely used to verify the position of catheters, tubes, and other support devices. Existing image models often return labels or segmentations, whil…
- arXiv cs.AIagentsSafe Skill Retirement for Physical Agents
arXiv:2609.29543v1 Announce Type: new Abstract: Agent skills bundle procedural guidance with execution conditions governing authority, user consent, and live environment state. When model capabilities advance, maintainer…
- arXiv cs.AIagentsERRAND: Budgeted Maintenance of Agent Memory
arXiv:2609.29545v1 Announce Type: new Abstract: Deployed agents run on handed-over knowledge: a frozen policy consults a briefing of consolidated items written before the stream begins. The world then moves while the sto…
- arXiv cs.AIresearchHiPACE: Hierarchical Phase-Boundary Analysis and Controlled Evaluation of Feature Absorption in Sparse Autoencoders
arXiv:2609.29551v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose LLM activations into sparse dictionary atoms, so that each distinct concept gets its own feature. One recurring behavior complicates th…