Search: “llm”

ValueGraph: Value-Signal Guided Graph Pre-training for Contextualized User Representation

arXiv:2609.00057v1 Announce Type: cross Abstract: Value signals are aggregated user-level moral representations that capture users' inferred value-related tendencies from their online discourse. User

2 Sept 2026

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VerNav: Verifier-First Low-Latency Vision-and-Language Navigation

DGX agent

arXiv:2609.00920v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) requires an agent to navigate through unseen 3D environments according to natural-language instructions. Explicit

model-releasesarxiv-cs-cv

2 Sept 2026

A collective capability boundary in frontier large language models on guideline-conformant and case-specific oncology decision-making

arXiv:2608.28592v1 Announce Type: new Abstract: Large language models (LLMs) achieve high scores on medical knowledge examinations, yet real-world oncology is not a knowledge test--it is a sequence of

AgenTRIM: Tool Risk Mitigation for Agentic AI

arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper to

AgentRx: Diagnosing AI Agent Failures from Execution Trajectories

arXiv:2602.02475v2 Announce Type: replace Abstract: AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy t

Amortizing intractable inference in large language models

arXiv:2310.04363v3 Announce Type: replace-cross Abstract: Autoregressive large language models (LLMs) compress knowledge from their training data through next-token conditional distributions. This lim

safetyarxiv-cs-cl

Argument-Aware Semantic Alignment of Normative Texts: A Toulmin-Based Neuro-Symbolic Approach

arXiv:2608.29529v1 Announce Type: cross Abstract: Semantic alignment between specialized normative texts is challenging when equivalent requirements use different terms, syntax, and levels of abstract

Augmenting Human Performance with an XR Agent Learning from Online Behavior and BCI Evidence

arXiv:2608.30369v1 Announce Type: new Abstract: We present OLIVE, a framework for adapting a foundation model to provide real-time assistance in temporally demanding, high-stakes, and dynamic tasks. W

Automatic Conversion of NICE Guidelines to an Executable Computational Model Using Large Language Models

arXiv:2608.30022v1 Announce Type: new Abstract: Introduction: NICE guidelines provide evidence-based recommendations for clinical care but remain largely in unstructured natural language. Existing app

Beyond Semantic Accuracy: Consequence-Aware Evaluation for Safety-Critical Language Understanding

arXiv:2608.24621v2 Announce Type: replace Abstract: Can language models be trusted in safety- critical operations? In such settings, strong per- formance on semantic metrics does not guaran- tee opera

BIRD-History: A Benchmark for History-Driven Text-to-SQL with Fine-Grained Knowledge Annotations

arXiv:2608.29345v1 Announce Type: new Abstract: While recent Large Language Model (LLM)-based text-to-SQL systems achieve impressive performance on standard benchmarks, they struggle when user queries

Brain-Language-Action (BLA) Models: Language-Conditioned EEG for Robotics Control

arXiv:2608.28967v1 Announce Type: cross Abstract: Electroencephalography (EEG)-based robotic control is commonly formulated as a direct classification problem, in which electrical neural signals are m

researcharxiv-cs-lg

Local Ai

CoMPASS: Collaborative Molecular Property Prediction via Adaptive Small-Large Model Synergy

arXiv:2608.30674v1 Announce Type: cross Abstract: Accurate molecular property prediction requires both statistical reliability and chemical reasoning. Graph neural networks can be calibrated directly

local-aiarxiv-cs-ai

DIASENTINEL: An Auditable Multi-Agent System for Guideline-Grounded Diabetes Risk Screening

arXiv:2608.31128v1 Announce Type: new Abstract: Large language models (LLMs) offer promising clinical decision support but remain vulnerable to hallucinated facts, unsupported recommendations, and cit

agentsarxiv-cs-cl

Do Large Language Models Possess a Theory of Mind? A Comparative Evaluation Using the Strange Stories Paradigm

arXiv:2603.18007v2 Announce Type: replace-cross Abstract: The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infe

Do large language models scrutinise what they review? A multimodal audit of scoring calibration, error detection, and author-identity effects

arXiv:2608.28626v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate peer reviews, prompting examination of their capacity for critical evaluation. This stu

Do VLMs Share Safety Neurons Across Modalities?

arXiv:2608.30750v1 Announce Type: new Abstract: Vision-language models (VLMs) can comply with harmful requests delivered through images, even when their LLM backbones would refuse the same content in

safetyarxiv-cs-lg

DS-Lighting: Making Agent Harnesses Explicit for Data-Science Automation

arXiv:2608.28590v1 Announce Type: new Abstract: Large Language Model (LLM) agents have shown promise for automating data-science workflows, yet their end-to-end performance depends critically on the a

Dynamic Important Example Mining for Reinforcement Finetuning

arXiv:2608.29252v1 Announce Type: new Abstract: Reinforcement fine-tuning (RFT) is increasingly used to strengthen the reasoning abilities of large models, yet its effectiveness is bound by how traini

Entropy-Aware Token Rejection for Improving Speculative Decoding

arXiv:2512.23765v2 Announce Type: replace-cross Abstract: Speculative decoding (SD) accelerates large language model (LLM) inference by using a lightweight draft model to propose tokens and a stronger

FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents

arXiv:2510.03204v2 Announce Type: replace Abstract: Web agents powered by large language models (LLMs) must process lengthy web page observations to complete user goals; these pages often exceed tens

researcharxiv-cs-cl

FRAMEWORKERS: A Dynamic Multi-Agent Framework for AI-Generated Video Production

arXiv:2608.29814v1 Announce Type: new Abstract: Modern video generators excel at synthesizing individual clips, but complete video production requires coordinating a long sequence of interdependent cr

Generating Clinical Vignettes that Preserve Cognitive Formulations

arXiv:2608.29995v1 Announce Type: cross Abstract: Large language models can generate fluent clinical case vignettes, but fluency alone does not ensure fidelity to a specifiable clinical structure. We

Hidden Threat in Synthetic Data: Covert Targeted Bias Injection through Benign Text

arXiv:2608.30619v1 Announce Type: cross Abstract: Synthetic data is increasingly used to train large language models (LLMs), yet its security implications remain poorly understood. Prior work on subli

Integrating adaptive human behavior into epidemic models with large language models

arXiv:2608.29535v1 Announce Type: cross Abstract: Infectious disease transmission is shaped by patterns of human interaction, which adapt as epidemic conditions change. Capturing these context-depende

JudgePanel: A Compact Judge with Panel Deliberation via Adaptive Multi-Reward Reinforcement Learning

arXiv:2608.29168v1 Announce Type: new Abstract: The LLM-as-a-Judge paradigm has emerged as a scalable alternative to human evaluation. However, single-model judges are limited by their inherent model

Learning to Follow In-Context Watermark Instructions via Self-Distillation

arXiv:2608.29030v1 Announce Type: new Abstract: In-context watermarking (ICW) prepends an instruction to a query asking the model to embed a statistically detectable signal in its response. It thus eq

MAGneT: Coordinated Multi-Agent Generation of Synthetic Multi-Turn Mental Health Counseling Sessions

arXiv:2509.04183v3 Announce Type: replace-cross Abstract: The growing demand for scalable psychological counseling highlights the need for high-quality, privacy-compliant data, yet such data remains s

Measure Before You Manage: Evaluating Agent Working Memory in Coding Agents

arXiv:2608.31057v1 Announce Type: new Abstract: Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated state play different semantic roles an

Oculi: A Conversational Agentic Platform for Automated Credit Risk Analysis

arXiv:2608.28944v1 Announce Type: new Abstract: Credit risk analysis in financial institutions traditionally requires analysts to manually write SQL queries, run statistical computations, and build vi

ReVA: A Region-Aware Visual Assistant for Visually Grounded Question Answering

arXiv:2608.28707v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in Visual Question Answering (VQA), yet they continue to struggle with questi

researcharxiv-cs-cl

SALT: Salience-Aware Lexical Trie for Long-Context Compression

arXiv:2607.17486v2 Announce Type: replace-cross Abstract: As large language models (LLMs) process increasingly longer prompts, computation and KV-cache memory costs have emerged as major bottlenecks i

Applications

SHAPE of Chain-of-Thought in Math Reasoning

arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their

applicationsarxiv-cs-ai

SinLlama -- A Large Language Model for Sinhala

arXiv:2508.09115v5 Announce Type: replace Abstract: Low-resource languages such as Sinhala are often overlooked by open-source Large Language Models (LLMs). In this research, we extend an existing mul

Local Ai

Small Language Models as Judges for Rubric-Based Reinforcement Learning

arXiv:2608.30005v1 Announce Type: new Abstract: Rubric-based reinforcement learning extends RL beyond tasks with exact answers or rule-based verifiers by scoring responses against instance-specific cr

local-aiarxiv-cs-cl

SPADE: A Large Language Model Framework for Soil Moisture Pattern Recognition and Anomaly Detection in Precision Agriculture

arXiv:2509.18123v2 Announce Type: replace Abstract: Accurate interpretation of soil moisture patterns is critical for irrigation scheduling and crop management, yet existing approaches for soil moistu

Standardizing Longitudinal Radiology Report Evaluation via Large Language Model Annotation

arXiv:2601.16753v2 Announce Type: replace-cross Abstract: Longitudinal information in radiology reports refers to the sequential tracking of findings across multiple examinations over time, which is c

Strong Drafts Need Compact Memories: Long-Context Speculative Decoding with Compressed KV Cache

model-releasesarxiv-cs-lg

arXiv:2608.30252v1 Announce Type: new Abstract: Long-context LLM applications such as document summarization and multi-turn agents require generation from prefixes spanning tens of thousands of tokens

SwarmBench: Can Large Language Models Act as Agent Swarm Orchestrators?

arXiv:2608.30661v1 Announce Type: new Abstract: Large language model-based multi-agent systems are evolving from fixed interaction topologies toward dynamically orchestrated Agent Swarms. However, exi

Test-Time Training with Next-Token Prediction

arXiv:2606.21803v2 Announce Type: replace Abstract: Next-token prediction is the self-supervised signal that trains language models, and every observed prompt token provides the same signal at test ti

The Hallucination Signal Is a Mean Shift: Why Simple Probes Suffice

arXiv:2608.28930v1 Announce Type: cross Abstract: Hidden-state probes effectively detect LLM hallucinations, but the geometry of the signal remains poorly characterized, driving increasingly complex p

Toward Cultural Alignment: Human-Centered Evaluation of Multimodal AI Stories Across Five African Communities

arXiv:2608.29209v1 Announce Type: new Abstract: In this paper, we examine how well AI-generated multimodal stories align with the lived practices, relationships, language, values, and visual expectati

safetyarxiv-cs-cl

Toward Latent Language Model Skills Steering and Optimization: An Empirical Study

arXiv:2608.29459v1 Announce Type: new Abstract: Skills, as a useful abstraction for the procedural capabilities of large language models (LLMs), capture how models perform structured, multi-step reaso

TrainSDC: Characterizing and Mitigating Silent Data Corruption in Large Language Model Training

model-releasesarxiv-cs-lg

arXiv:2608.30769v1 Announce Type: new Abstract: LLM training is increasingly vulnerable to silent data corruption (SDC), yet existing protection methods largely treat Transformer computations uniforml

Using Grounded Theory for Agent Behavior Analysis at Scale

arXiv:2608.30391v1 Announce Type: cross Abstract: Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, often unfamiliar tasks where p

VERA: Authority-Preserving Edge Revocation for Federated AI-Agent Workflows

arXiv:2608.30091v1 Announce Type: new Abstract: Modern agent frameworks compose planners, tool agents, remote services, and shared specialists into runtime delegation graphs, but their revocation APIs

Local Ai

Where Identity Lives: Localized, Retain-Free Identity Unlearning in Multimodal Large Language Models

arXiv:2608.30649v1 Announce Type: new Abstract: Removing a specific individual's information from multimodal large language models (MLLMs) is often needed after deployment, but existing methods rely o

local-aiarxiv-cs-cl

WildSEEK: Evaluating Language Models for Information-Seeking

arXiv:2608.30683v1 Announce Type: new Abstract: Language models are increasingly mediating information access to end users, urging a systematic evaluation of their responses for a fair and reliable in

safetyarxiv-cs-cl