News / #agents Tag Agents + tool use 500 articles archived under #agents · RSS Sign in to follow arXiv — Machine Learning research 10d ago Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning arXiv:2608.00301v1 Announce Type: new Abstract: Error-penalized scoring rules ($+1$ for a correct answer, $-\lambda$ for a wrong one, $0$ for abstaining) are increasingly prescribed against hallucination: a rational agent facing such a rule answers exactly when its correctness… 37 arXiv — Machine Learning research 10d ago Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch arXiv:2608.00316v1 Announce Type: new Abstract: Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic statistical priors. Richer domain priors can improve BO in principle,… 20 arXiv — Machine Learning research 10d ago Agentic Graph Token Reasoning arXiv:2608.00542v1 Announce Type: new Abstract: Graphs model relational data throughout science and industry, from citation networks to product co-purchase graphs. Because the nodes of many such graphs carry rich text, a growing line of work applies large language models (LLMs)… 11 arXiv — Machine Learning research 10d ago AdvPlan-Bench: Adversarial Evaluation of Structured Plan-Generation Agents arXiv:2608.00832v1 Announce Type: new Abstract: Structured plan-generation agents are often evaluated as if a plan has quality in isolation, yet many realistic planning tasks require asking how a candidate behaves when another agent can search for responses. We introduce… 27 arXiv — Machine Learning research 10d ago AOSpec: Action and Observation Co-Speculation for Low-Latency Agent Serving arXiv:2608.00881v1 Announce Type: new Abstract: Large language model agents increasingly act through stateful tools, yet model generation and environment execution remain serialized at every step. As decoding accelerates, tool execution becomes a growing bottleneck. Existing… 20 arXiv — Machine Learning research 10d ago Stop When Memory Suffices: Evidence-Conditioned Progressive Execution for LLM Agents arXiv:2608.01285v1 Announce Type: new Abstract: The continued development of LLMs toward persistent and adaptive intelligence increasingly requires long-term memory mechanisms that preserve and reuse information across interactions. Existing memory systems either compress and… 21 arXiv — Machine Learning research 10d ago HindSearch: Trajectory-Level Hindsight Critique for Search-Augmented Reinforcement Learning arXiv:2608.01597v1 Announce Type: new Abstract: Search-augmented LM agents are typically trained with a binary exact-match reward, which throws away most of what a failed trajectory tells us about why it failed. We introduce HindSearch, a hindsight self-distillation procedure… 14 arXiv — Machine Learning research 10d ago Progressive Agent Skill Generation via Reinforcement Learning arXiv:2608.01678v1 Announce Type: new Abstract: Existing skill generation methods largely rely on heuristics or pipeline-style consolidation, which must be specially designed for different evidence sources. In contrast, learning-based approaches offer a more unified way to model… 6 arXiv — NLP / Computation & Language research 10d ago MemoryForge: Synthesize Lifelong Memory for Human-Like LLM Agents arXiv:2608.00007v1 Announce Type: new Abstract: Equipping Large Language Models (LLMs) with human-like personas is crucial for agentic applications, such as role-play and user simulation. Traditional prompt-based methods rely on descriptive conditioning by injecting static… 16 arXiv — NLP / Computation & Language research 10d ago AgentMemBench: A Systematic Benchmark for Evaluating Long-Term Memory Management Strategies in Conversational AI Agents arXiv:2608.00009v1 Announce Type: new Abstract: Long-term memory remains a critical bottleneck for conversational AI agents, whose finite context windows cannot support coherent recall across thousands of turns. We present AgentMemBench, a unified, reproducible benchmark… 32 arXiv — NLP / Computation & Language research 10d ago Role Steering of Language Models for Social Simulations arXiv:2608.00023v1 Announce Type: new Abstract: Social simulations built from language-model agents need role-conditioned behavior that can be checked before agents are placed into a simulated population. We introduce an activation-steering screening workflow for… 29 arXiv — NLP / Computation & Language research 10d ago SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach arXiv:2608.00030v1 Announce Type: new Abstract: Specialised retrieval agents typically surface higher quality results than general-purpose search, but selecting the optimal agent for a given query remains an open problem. Current approaches route queries based on inferred topic… 8 arXiv — NLP / Computation & Language research 10d ago A Few Neurons Reveal When LLMs Misuse Tools: Sparse Detection and Selective Steering for Reliable Tool Use arXiv:2608.00218v1 Announce Type: new Abstract: Agentic LLMs exhibit three consequential tool-use failures: invalid arguments (validity), unnecessary calls (over-calling), and omitted calls when tools are needed (missing). We find that a small, failure-specific set of MLP… 25 arXiv — NLP / Computation & Language research 10d ago CurveShift: Is Agent Progress Scalar? Separating Level from Shape arXiv:2608.00355v1 Announce Type: new Abstract: Progress in large language models is often summarized using a single scalar measure, such as a time horizon, a latent ability estimate, or an aggregate benchmark score. These summaries capture the overall performance, but they do… 6 arXiv — NLP / Computation & Language research 10d ago Deep Research Pretraining via Predictive Navigation arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, and report evaluation. We introduce Deep Research Pretraining (DRP), an offline… 8 arXiv — NLP / Computation & Language research 10d ago SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods use execution correctness only as a trajectory-level reward, which provides… 32 arXiv — NLP / Computation & Language research 10d ago OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution arXiv:2608.00677v1 Announce Type: new Abstract: AI agents operate in persistent environments where early state changes can influence decisions far into the future. Unlike conventional language-model interactions, agent behavior is mediated through a shared state that is… 14 arXiv — NLP / Computation & Language research 10d ago Practical Online KV Cache Compaction for LLM Agents: An Empirical Study arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV cache compaction can reduce this cost, but most prior methods assume a static… 33 arXiv — NLP / Computation & Language research 10d ago ACE-GraphRAG: Agentic Context Engineering for Hierarchical GraphRAG arXiv:2608.01269v1 Announce Type: new Abstract: Hierarchical Graph Retrieval-Augmented Generation (GraphRAG) organizes corpus knowledge at multiple levels of granularity, yet fixed context construction may fail to translate these multi-resolution representations into a context… 28 arXiv — NLP / Computation & Language research 10d ago BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent arXiv:2608.01321v1 Announce Type: new Abstract: Multi-step search is a fundamental capability for search agents, enabling them to iteratively acquire, refine, and integrate external evidence for complex reasoning QA. However, vanilla GRPO allocates rewards exclusively based on… 5 arXiv — NLP / Computation & Language research 10d ago Prompt-Induced Waste in Large Reasoning Models: A Preregistered Two-Harness Benchmark of Coding Agents arXiv:2608.01347v1 Announce Type: new Abstract: Large reasoning models used as coding agents incur costs from deliberation, tool calls, and repeated agent turns, yet the causal effect of prompt wording on this spend has not been measured systematically. We present a… 36 arXiv — NLP / Computation & Language research 10d ago HopRefusalBench: Diagnosing Refusal Failures in Search-Augmented Agents for Multi-Hop Reasoning arXiv:2608.01358v1 Announce Type: new Abstract: Search-augmented large language model agents are increasingly capable of solving knowledge-intensive tasks, but their behavior when a multi-hop question is fundamentally unanswerable remains poorly understood. Existing abstention… 33 arXiv — NLP / Computation & Language research 10d ago EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents arXiv:2608.01359v1 Announce Type: new Abstract: Outcome-based reinforcement learning enables search-augmented language agents to learn from verifiable final answers, but its trajectory-level credit cannot distinguish the contributions of individual actions in a multi-turn search… 8 arXiv — NLP / Computation & Language research 10d ago Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+ arXiv:2608.01395v1 Announce Type: new Abstract: We evaluate large language models (LLMs) as language agents playing goal-directed dialogue games in self-play across 30 languages: the 24 official EU languages plus six others. Unlike static or preference-based evaluation, this… 5 arXiv — NLP / Computation & Language research 10d ago DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering arXiv:2608.01565v1 Announce Type: new Abstract: Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers structured retrieval but typically uses fixed traversal, while agentic RAG… 21 arXiv — NLP / Computation & Language research 10d ago PGMem: Tightly Coupled Persona-Memory Graph for Lifelong Personalized Agents arXiv:2608.01708v1 Announce Type: new Abstract: Long-term personalized dialogue agents must track user preferences as their personas evolve. Existing memory systems organize past events well, but store personas as flat profiles detached from the events that justify them. This… 5 Vercel — AI dev-tools 10d ago Give your eve agent a browser Your eve agent can now navigate the web like a human with agent-browser . The @agent-browser/eve extension gives any eve agent a full set of browser tools: navigate pages, read content, click, fill forms, take screenshots, and inspect console and network activity. Everything… 33 Vercel — AI dev-tools 10d ago Skill packs are now available on skills.sh You can now bundle multiple agent skills into a shareable pack on skills.sh . Hand anyone a curated set via a single URL, or share it with your GitHub organization to standardize the skills your team's agents use across any project. Create a pack from community skills on… 25 Hugging Face Daily Papers research 10d ago SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation Abstract Agent skills have become an important mechanism for equipping language-model agents with reusable procedural knowledge. However, providing skills alone does not guarantee that current models can effectively identify, apply, and coordinate them. To improve skill-use… 11 Hugging Face Daily Papers research 10d ago SWE-Touch: Benchmarking Coding Agents When Users Touch the Code Abstract Real-world software development requires coding agents to operate in shared workspaces where users may inspect and modify code during an ongoing task, yet existing repository-level benchmarks typically evaluate agents working alone or restrict user participation to… 38 Hugging Face Daily Papers research 10d ago ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step Abstract To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone, even in the absence of documentation. However, existing tool-use benchmarks expose semantic tool schemas in static… 24 r/LocalLLaMA community 10d ago NousResearch keeps doing things on hermes Has anyone followed nousresearch work on Hermes? I mean we are Q3 2026. We have some crazy models trickling down from HGX territory to multi gpu workstation. And we have nousresearch deploying the 0.20 of its hermes agent while starting releasing the project with a 0.2 mid… 13 r/LocalLLaMA community 10d ago G9v3-39A5B: Agentic heavy MOE with low hallucination Hugging Face Artificial Analysis Should be a sweet spot for general work. Seems like coding is the only part that is inferior to Qwen.   submitted by   /u/axseem [link]   [comments] 16 NVIDIA Developer Blog official-blog 10d ago NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage Storage is an active part of every agentic AI workflow. As agents retrieve enterprise knowledge, access persistent memory, reuse key-value (KV) cache data,... 17 Hugging Face Daily Papers research 11d ago EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents Abstract The web is increasingly accessed by AI agents rather than humans. Every agent needs knowledge, especially in the life-sciences, where agentic pipelines are growing fast. Access to the literature is a crucial part of that need, and resources such as Europe PMC, with over… 14 MIT Technology Review — AI news-outlet 11d ago Here’s why AI agents lie and cheat to reach their goals MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. When two OpenAI models hacked into the website Hugging Face in July, they weren’t trying to make… 37 Hugging Face Daily Papers research 11d ago ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction Abstract Enterprise workflows increasingly rely on agents for schema-guided extraction: given a document and a user-defined schema, the agent faithfully follows the schema to produce the correct output with source evidence as grounding metadata. We present ExtractBench, a… 4 arXiv — Machine Learning research 11d ago Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations arXiv:2607.28826v1 Announce Type: new Abstract: Autonomous Cyber Operations (ACO) are increasingly important for defending enterprise networks as cyber threats continue to evolve in sophistication. ACO applications commonly employ Reinforcement Learning (RL) agents to learn… 24 arXiv — Machine Learning research 11d ago An analysis of machine learning approaches for enhancing decision-making in complex discrete choice tasks arXiv:2607.28854v1 Announce Type: new Abstract: Discrete choice modeling is a common tool used for preference elicitation during policy-making, but this is typically done through parametric models. Machine learning can push the boundaries of discrete choice modeling for… 18 arXiv — Machine Learning research 11d ago Autonomous Repair for Multi-Agent Systems via Monte-Carlo Tree Search arXiv:2607.29055v1 Announce Type: new Abstract: Multi-agent systems (MAS) are increasingly deployed to solve complex tasks. In case of incorrect or unsatisfactory outputs, users have to manually locate agent mistakes by inspecting agent trajectories (i.e., {\em failure… 9 arXiv — Machine Learning research 11d ago DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation arXiv:2607.29078v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models on their own rollouts to reduce exposure bias. However, in multi-turn agent scenarios, early student errors can lead a trajectory away from the teacher's familiar domain. Existing… 11 arXiv — Machine Learning research 11d ago SERUM: State Extraction and Refinement for User Modeling arXiv:2607.29181v1 Announce Type: new Abstract: Agentic assistants capable of proactive, personalized interactions require structured models of user intent and workflow. However, building these models from raw, unstructured screen activity remains an open challenge. We present… 34 arXiv — Machine Learning research 11d ago When Does On-Policy Interaction Help? Representational Tradeoffs in Value-Based Imitation Learning arXiv:2607.29617v1 Announce Type: new Abstract: Imitation learning (IL)---training an agent to replicate expert behavior from demonstrations---underpins applications from robotics to language model training. Standard approaches such as Behavior Cloning (BC) are known to suffer… 24 arXiv — NLP / Computation & Language research 11d ago Learning Stateful Predictive Knowledge From Experience arXiv:2607.28638v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly learn from experience, they primarily rely on trajectory-level reflection to extract insights. Viewed through the lens of predictive knowledge, we argue that this approach operates… 30 arXiv — Machine Learning research 11d ago When Unlearning Fails: Reliable Data Deletion under Post-Training in Agent Networks arXiv:2607.28829v1 Announce Type: cross Abstract: Self-improving federated agent networks keep training after deployment by collecting new trajectories with the current policy and feeding them back into later rounds. This closed loop makes unlearning harder than a one-time model… 25 arXiv — NLP / Computation & Language research 11d ago The Formalism Trap: Are LLM-as-a-Judge Evaluators Blinded by Consensus Mimicry under Social Load? arXiv:2607.28641v1 Announce Type: new Abstract: We introduce the \textit{Agentic Formalism Trap} and the Evaluative Dissonance Index ($D_E$), quantifying how LLM-as-a-Judge systems conflate structural proceduralism with semantic truth under adversarial load. Analyzing 22,500… 8 arXiv — NLP / Computation & Language research 11d ago Self-Supervised Skill Optimization arXiv:2607.28777v1 Announce Type: new Abstract: Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized with ground-truth (GT) feedback. Many applications, however, lack GT labels,… 27 arXiv — NLP / Computation & Language research 11d ago Benchmarks Are Not Validation: A System-Level View of Financial LLM Applications arXiv:2607.28840v1 Announce Type: new Abstract: Large language models are increasingly deployed in financial applications that combine retrieval, proprietary data, tool use, orchestration logic, monitoring, and human escalation. Yet evaluation often remains model-centric:… 26 arXiv — NLP / Computation & Language research 11d ago Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding arXiv:2607.29196v1 Announce Type: new Abstract: Long-running multi-turn interactions with chatbots and agents are now common, and a correct response often depends on remembering earlier details, tracking later revisions, identifying intended objects or referents, and withholding… 19 arXiv — NLP / Computation & Language research 11d ago Data Turnstile: A Scalable Open Framework for Function-Calling Data Generation arXiv:2607.29250v1 Announce Type: new Abstract: Small language models (SLMs) are attractive for agentic deployment due to low latency, reduced cost, and on-device privacy, yet they struggle with tool-use tasks where training data is scarce and noisy. Unlike larger models, SLMs… 13 Page 8 of 10 · 500 articles ← Newer Older →
