Search: “llm”

You Can't Escape Your Own Activations : Evaluation Awareness and Multi-Agent Monitoring

arXiv:2609.03035v1 Announce Type: cross Abstract: LLM agents are increasingly deployed in multi-agent systems, where they can collude while keeping their actions benign. Output monitors designed to de

agentsarxiv-cs-lg

4 Sept 2026

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Are Non-English Papers Reviewed Fairly? Language-of-Study Bias in NLP Peer Reviews

DGX agent

arXiv:2604.07119v2 Announce Type: replace Abstract: Peer review plays a central role in the NLP publication process, but is susceptible to various biases. Here, we study language-of-study (LoS) bias:

safetyarxiv-cs-cl

3 Sept 2026

CHIME: Credit-Aware Hierarchical Memory Evolution for Long-Horizon Agentic Planning

arXiv:2609.02074v1 Announce Type: new Abstract: Planning is a central capability that enables agents to decompose complex long-horizon tasks into manageable steps. Test-time search and training-based

CHisAgent: A Multi-Agent Framework for Event Taxonomy Construction in Ancient Chinese Cultural Systems

arXiv:2601.05520v2 Announce Type: replace Abstract: Despite strong performance on many tasks, large language models (LLMs) show limited ability in historical and cultural reasoning, particularly in no

safetyarxiv-cs-cl

Local Ai

Coverage, Not Targeting: A Structural Regime in Multi-Turn Agent Credit Assignment

arXiv:2609.02417v1 Announce Type: cross Abstract: Multi-turn agentic RL increasingly treats credit assignment as a targeting problem: given a terminal verifiable reward, per-turn methods localize cred

local-aiarxiv-cs-ai

CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing

arXiv:2609.01925v1 Announce Type: cross Abstract: The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a severe computational bottleneck. Traditiona

researcharxiv-cs-cl

Do Large Language Models Capture the Diversity in their Training Data?

arXiv:2609.02275v1 Announce Type: cross Abstract: Large language models are trained to model conditional distributions over text, yet it remains inadequately understood whether they capture the full d

EarlyEval: Cheaper Agent Evaluation via Early Outcome Prediction

arXiv:2609.02783v1 Announce Type: new Abstract: Evaluating LLM agents is essential for guiding their development, yet it has grown prohibitively expensive: a single pass of a frontier model over an ag

Tutorials

EmoStance: Response-Side Affective-Orientation Control for Empathetic Response Generation via Emoji Weak Supervision

arXiv:2609.02133v1 Announce Type: new Abstract: Empathetic response generation requires models to decide not only what to say, but also how to respond to the previous speaker's affective situation. We

tutorialsarxiv-cs-ai

Gauge dependence and structured-output corruption in sign-branched repetition penalties: measurements across models, inference stacks, and alternative repetition controls

arXiv:2607.09791v2 Announce Type: replace-cross Abstract: The multiplicative repetition penalty shipped across the LLM inference ecosystem (HuggingFace, vLLM, llama.cpp, and a dozen further engines) b

HyperStyler: Low-resource Authorship Style Transfer via Context-aware Style Navigation and Hypernetworks

arXiv:2609.02772v1 Announce Type: new Abstract: Low-resource authorship style transfer (LAST) aims to rewrite text into the style of an arbitrary target author using only a few reference examples whil

Improving Health Literacy through Lay Summarization of Radiological Reports: An Evaluation of BioNER and Retrieval-Augmented Generation

arXiv:2609.02396v1 Announce Type: new Abstract: Radiology reports are written primarily for clinicians, and their specialized terminology often makes them difficult for patients to interpret. As a res

Measurement-Driven Sub-Network Selection for On-Premise Retrieval-Augmented Factory Agents

arXiv:2609.02760v1 Announce Type: new Abstract: On-premise assistants can give factory workers conversational access to machine documentation, but models capable of the task rarely fit shop-floor hard

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

OSDAG: Online Scheduling for Efficient Multi-Robot Collaboration

model-releasesarxiv-cs-ro

arXiv:2606.15255v2 Announce Type: replace Abstract: Coordinating heterogeneous multi-robot systems (MRS) for complex, long-horizon tasks requires both flexible high-level reasoning and efficient execu

PGPO: Potential-Guided Policy Optimization for Multi-Turn Agentic Tasks

arXiv:2609.02236v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has become an effective paradigm for LLM post-training, but in multi-turn agentic tasks with sparse terminal rew

Tutorials

Prompting the Unknown: Understanding Response Uncertainty in Large Language Models

arXiv:2407.14845v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used in decision-making across diverse domains. Ensuring the generation of safe and reliable responses

tutorialsarxiv-cs-cl

Public-Sharing Labels and Verbatim Field Egress in an MCP-to-A2A Agent Configuration: A Controlled Multi-Model Study

arXiv:2609.01693v1 Announce Type: cross Abstract: Safety properties assessed separately for Model Context Protocol (MCP) tool use and Agent2Agent (A2A) delegation need not describe behavior when one a

SafeEvolve: Harness-Policy Co-Evolution from Agent Experience for Safety Alignment

arXiv:2609.02786v1 Announce Type: new Abstract: The performance of LLM-based agents is jointly shaped by the base model and the harness used when interacting with the environment. This exposes them to

text2ql: Multi-Target Natural Language Querying via a Language-Agnostic Intermediate Representation

arXiv:2609.02115v1 Announce Type: cross Abstract: Natural language interfaces to databases have traditionally suffered from three structural limitations: exclusive targeting of relational SQL, uncondi

WinoQueer-NL: Assessing Bias in Dutch Language Models toward LGBTQ+ Identities

arXiv:2609.02651v1 Announce Type: new Abstract: While English language models have been widely examined for anti-queer bias, Dutch models remain understudied. To address this gap, we developed a cultu

A Classifier That Teaches Itself: Self-Improving, Frozen-gate Training (SIFT) for Dynamic Document Classification

arXiv:2607.18358v2 Announce Type: replace Abstract: Document classification is a solved problem in the laboratory and an unsolved one in the enterprise. The blocker is rarely model architecture; it is

safetyarxiv-cs-cl

A Dataset for Modeling Iterative Problem-Solving

arXiv:2609.00940v1 Announce Type: new Abstract: Solving problems through repeated attempts is a sequential modeling task: at each step, the solver receives feedback and decides how to revise their sol

Analog-DB: An Agent-First Analog Integrated Circuit Database, From Blocks to Systems

arXiv:2609.01286v1 Announce Type: new Abstract: Sharing analog integrated circuit designs remains difficult: foundry non-disclosure agreements restrict the process details a design depends on, and the

APEX-EM: Non-Parametric Online Learning for Autonomous Agents via Structured Procedural-Episodic Experience Replay

arXiv:2603.29093v3 Announce Type: replace-cross Abstract: LLM agents rerun full reasoning for every task, even one they solved moments earlier. We introduce extbf{APEX-EM}, a non-parametric experience

agentsarxiv-cs-ai

Applications

Autoresearch for Marketplace Catalogs: From Legacy Forms to AI-Native Matching

arXiv:2609.00274v1 Announce Type: new Abstract: Two-sided service marketplaces are moving from deterministic request-form intake to AI-native probabilistic matching, enabled by large language models (

applicationsarxiv-cs-ai

Capability-Gated Language Models: Security Composes, Utility Does Not

arXiv:2609.00445v1 Announce Type: cross Abstract: Deployed language model safeguards (safety fine-tuning, filtering, unlearning) vary by principal only outside the model weights: filters are reconfigu

Hardware

Closing Cost-Quality Gap in Document VLMs: Difficulty-Aware Data Curation and Quality-Adjusted Deployment Economics

arXiv:2609.01575v1 Announce Type: new Abstract: Extracting structured fields from hundreds of millions of documents annually remains costly in regulated industries: bespoke OCR cascades cover only a f

hardwarearxiv-cs-cl

Data-Driven Persona-Conditioned Agents for A/B Test Simulation

arXiv:2609.01038v1 Announce Type: new Abstract: A/B testing is the gold standard for evaluating product changes, but each experiment requires real user traffic, engineering effort, and weeks of measur

DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference

model-releasesarxiv-cs-lg

arXiv:2609.00407v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language model (LLM) inference but suffer from substantial data-movement overhead wh

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

Evaluating Style-Personalized Text Generation: Challenges and Directions

arXiv:2508.06374v4 Announce Type: replace Abstract: With the surge of large language models (LLMs) and their ability to produce customized output, style-personalized text generation--'write like me'--

EvoSCM: Scientific Belief Revision Through Causal Model Evolution and Experimentation

arXiv:2609.01526v1 Announce Type: new Abstract: Scientific agents must learn not only how to reason, but also what to believe. However, existing LLM agents typically express scientific hypotheses in f

Explore More, Drift Less: Outcome-Only Reinforcement Learning Can Suffice for Long-Horizon Interactive Agents

arXiv:2609.01245v1 Announce Type: cross Abstract: Reinforcement learning is a natural way to post-train LLM agents for long-horizon interactive tasks judged only by end-of-task verification, yet a sha

Local Ai

Federated Trust for Embodied Robot Capability Marketplaces

arXiv:2609.00404v1 Announce Type: cross Abstract: Robot capability marketplaces, the 'app store for robot skills,' are emerging as the deployment vector for LLM-driven robot fleets. The default cloud-

local-aiarxiv-cs-ro

Harness-of-Harness: Multi-Day Autonomous Software Development with Continual Improvement

arXiv:2609.01481v1 Announce Type: new Abstract: This paper studies autonomous software development, in which LLM-based coding agents transform high-level requirements into complete, functional, and us

Hints Help But Do They Teach? Evaluating Skills Transfer in Code Generation

arXiv:2609.01106v1 Announce Type: cross Abstract: When a hint turns a failing generated program into a passing one, does it provide missing information or merely steer the model toward a solution it c

Hypotheses-Guided Self Distillation for Continual Personalization

arXiv:2609.00251v1 Announce Type: new Abstract: As people increasingly interact with LLM assistants in daily life, continually adapting to individual preferences has become essential for effective lon

Investigating Linear Probe Robustness to Linguistic Register, Medical Specialty, and Corpus Shifts in Medical QA

arXiv:2609.01361v1 Announce Type: new Abstract: Linear classifiers trained on hidden states of a large language model (LLM), linear probes, can flag factual errors from a single forward pass. Geometri

Iterative GRPO: Batch-Online Policy Iteration for Multi-Turn RL via Single-Turn RLHF

arXiv:2511.21638v2 Announce Type: replace Abstract: Practical LLM agents often operate over multi-turn conversations where success is determined only after the full interaction ends. Most multi-turn R

safetyarxiv-cs-lg

Modelpedia: A Catalog of Model Findings for the Meta-Science of AI

arXiv:2609.01090v1 Announce Type: new Abstract: Scientific knowledge about AI models is produced faster than the community can organize it. Every few months a new foundation model reshapes the field a

researcharxiv-cs-lg

Neuro-Symbolic Geometric Abstraction (NeuSOGA): From Observations to Symbolic Mathematical Representations

arXiv:2609.01408v1 Announce Type: new Abstract: A fundamental challenge in artificial intelligence is the transformation of observations into explicit symbolic representations suitable for abstraction

One Policy, Any Budget: Internalizing Budget-Aware Search via Reinforcement Learning

arXiv:2609.00813v1 Announce Type: new Abstract: While reinforcement learning has enabled LLM-based search agents to invoke external tools, existing methods train under fixed budgets and cannot adapt w

OUTLETS: Output-Length Prediction from Speculative Decoding Backbones

arXiv:2609.01068v1 Announce Type: new Abstract: The heavy-tailed distribution of output lengths in Large Language Model (LLM) serving poses major challenges for resource provisioning and cluster sched

researcharxiv-cs-cl

PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition

arXiv:2609.01024v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures scale Large Language Model (LLM) capacity efficiently by activating a sparse subset of experts per token. However

researcharxiv-cs-cl

The Irreversibility Budget: Fleet-Level Risk Accounting and Admission Control for Agent Operating Systems

arXiv:2609.00275v1 Announce Type: new Abstract: Fleets of LLM agents now externalize effects that cannot be fully undone: they move money, deploy code, delete data, and disclose information. Current c

agentsarxiv-cs-ai

The zbMATH Open Knowledge Graph: Tracing Centuries of Mathematical Research

arXiv:2609.00969v1 Announce Type: cross Abstract: We present the zbMATH Open Knowledge Graph, a large-scale RDF knowledge graph (KG) covering more than 250 years of mathematical scholarship. Unlike ex

Toward Workflow-Aware Benchmarking for Healthcare NLP Agents

arXiv:2609.00296v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly proposed for healthcare tasks such as clinical documentation, evidence retrieval, patient messaging,

agentsarxiv-cs-cl