Search: “llm”

Memory-First Fact-Checking: A Knowledge-Graph-Grounded Multi-Agent System for Misinformation Detection

arXiv:2608.29617v1 Announce Type: cross Abstract: This paper introduces a hybrid fact-checking framework that integrates Knowledge Graph-based semantic memory with adversarial multi-agent reasoning fo

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MineCEraft: Evaluating Language Models as Construction Engineers in the World of Minecraft

DGX agent

arXiv:2608.28884v1 Announce Type: new Abstract: We introduce MineCEraft (Minecraft Construction Engineering Benchmark, pronounced mine-see-ee-raft), an easy-to-use, open-source benchmark designed to s

model-releasesarxiv-cs-ai

1 Sept 2026

Mixture-Greedy for Online Generative Model Selection: Is UCB Necessary in Diversity-Aware Multi-Armed Bandits?

arXiv:2603.21716v2 Announce Type: replace-cross Abstract: Efficient selection among multiple generative models is increasingly important in modern generative AI, where sampling from suboptimal models

Applications

Modality Disentangled Learning for Incomplete Multimodal Emotion Recognition: A Primitive Memory Distillation Perspective

arXiv:2608.30563v1 Announce Type: new Abstract: Multimodal Emotion Recognition (MER) systems often suffer from missing modalities in real-world scenarios. Existing methods usually generate, align, or

applicationsarxiv-cs-cv

Modality Fault Lines: Structural Corruptions Reveal Fragile Omni-Modal Reasoning

arXiv:2608.29278v1 Announce Type: new Abstract: Omni-modal large language models are increasingly evaluated on clean text--vision--audio inputs, where every channel is present, synchronized, and readi

researcharxiv-cs-cl

Motus2: A Self-Evolving General World Model for Dexterous Manipulation

arXiv:2608.30237v1 Announce Type: cross Abstract: General embodied agents should perceive, predict, act, evaluate, and improve within a unified system. World models have shown great promise in buildin

Applications

Moving the Mean Toward the Known Good, Not Beyond It: What Inference-Time Interventions and Weight Consolidation Buy in Open-Ended Generation

arXiv:2608.28886v1 Announce Type: cross Abstract: What does a generation loop gain from learning on its own verified successes? In cycles of generate, verify, select and LoRA-consolidate on online bin

applicationsarxiv-cs-ai

Multimodal Large Language Models Predict Urban Safety Perception but Encode Non-Neutral Demographic Priors

arXiv:2503.00610v2 Announce Type: replace-cross Abstract: Understanding how people perceive urban environments is essential for inclusive planning, yet conventional surveys are costly and difficult to

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

arXiv:2607.19313v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on diffic

One Capability or Many? Testing the Economic Validity of Frontier AI Evaluation

arXiv:2608.29420v1 Announce Type: new Abstract: Frontier-model leaderboards now rank systems based on economic benchmarks, tests of how well models carry out professional tasks from software engineeri

OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques

arXiv:2608.31137v1 Announce Type: new Abstract: Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding

Ontology-Guided Multi-Agent Extraction of Evaluation Objects from Academic Review Texts: Evidence from Chinese Library and Information Science

arXiv:2608.29526v1 Announce Type: new Abstract: Academic reviews, scholarly commentaries, and book reviews serve as sources of evaluative statements about theories, methods, literature, institutions,

agentsarxiv-cs-cl

ORDDAR: Observation-Driven Reasoning for Distortion-Resilient Decision, Action, and Cognitive Recovery

arXiv:2608.28704v1 Announce Type: new Abstract: AI agents increasingly perform long-term reasoning, planning, tool use, memory integration, and autonomous decision making, yet erroneous intermediate s

Overreliance on AI in Information-seeking from Video Content

arXiv:2603.19843v2 Announce Type: replace-cross Abstract: The ubiquity of multimedia content is reshaping online information spaces, particularly in social media environments. At the same time, search

safetyarxiv-cs-cl

PokaiTrainer: Scaling Belief-State Search to Competitive Pokemon VGC

arXiv:2608.29197v1 Announce Type: cross Abstract: Decision-time equilibrium search carried poker to superhuman play, but it has so far relied on tractable subgames: a handful of actions per decision,

PRACTICE: From Experience to Expertise in Self-Evolving Embodied Agents

arXiv:2608.30760v1 Announce Type: new Abstract: Recent studies have shown that multimodal large language models (MLLMs) can serve as embodied agents, translating language instructions and visual obser

safetyarxiv-cs-lg

PrivBench: A Holistic and Modular Benchmarking Platform for Evaluating Text-to-Text Privatization

arXiv:2608.29624v1 Announce Type: new Abstract: Natural Language Processing methods have enabled novel solutions and advances in the field of privacy, particularly in the sub-domain of text-to-text pr

RACER: Reinforced Agent Collaboration for Explainable Reasoning on Knowledge Graphs

arXiv:2608.29263v1 Announce Type: new Abstract: Large Language Models (LLMs) often suffer from hallucination and struggle with complex reasoning tasks requiring multi-hop domain knowledge. While integ

Reactivating Test-Time Scaling for Plane Geometry Problem Solving

arXiv:2608.30156v1 Announce Type: new Abstract: Plane geometry problem (PGP) solving has become a critical benchmark for multimodal reasoning because it requires accurate visual perception and precise

Reference-Grafting Matches Fine-Tuning at Eliciting Sandbagged Capabilities

arXiv:2608.29458v1 Announce Type: cross Abstract: Sandbagging, in which a model deliberately underperforms on an evaluation despite retaining the underlying capability, threatens the safety evaluation

REIGN: Refurbished Embeddings with Integrated Guidance Networks for Efficient Context-Length Scaling

arXiv:2608.29899v1 Announce Type: cross Abstract: Dense retrieval over long documents is expensive. Token-level encoders scale quadratically in sequence length, and most long-context embedding models

RENSA: Rich Environment Metadata to Navigate Shared and Distributed Endpoints for Automated Federated SPARQL Query Generation

arXiv:2608.28963v1 Announce Type: cross Abstract: The number of knowledge graph databases has increased significantly with the proliferation of knowledge graph technologies. Knowledge graphs enable th

Review Before Trust: Source-Grounded Integrity Gates for AI-Assisted Personal Health Records

arXiv:2608.29965v1 Announce Type: new Abstract: Large language models can convert medical documents into structured data, but plausible output may still be unsupported by the source. Persisting such o

RouteSparse: Input-Conditional Pattern Routing for Budgeted Long-Context Prefilling

arXiv:2608.29058v1 Announce Type: new Abstract: Dynamic sparse attention can reduce the quadratic cost of long-context prefilling without changing model weights. MInference assigns each attention head

Scaffolding Foundation Models into Physical-World Agents Pushes the Frontier of Long-Horizon Navigation

arXiv:2608.30396v1 Announce Type: new Abstract: Long-horizon physical-world agents must reason over distant goals while grounding decisions in reliable closed-loop behavior. Today's foundation models

ScalePRM: Training Process Reward Models by Scaling Verification Compute Without Ground Truth

arXiv:2512.03244v2 Announce Type: replace-cross Abstract: Training process reward models (PRMs) requires step-level correctness labels, obtained either through expensive human annotation or by relying

Science sandboxes measure the scientific capability of AI agents

arXiv:2608.30165v1 Announce Type: cross Abstract: Scientific progress depends not only on finding solutions, but on learning the rules that explain why they work and using that understanding to design

Securing Amazon Quick from POC to production: Agents, Flows, and Spaces

Amazon Quick proof-of-concept projects often stall when security teams review the production plan. This post walks through designing dashboards, Spaces, knowledge bases, agents, and Flows with securit

agentsaws-ml-blog

Selection-Aware Stress Testing for Interactive Agents

arXiv:2608.30916v1 Announce Type: new Abstract: Agent evaluations often use one benchmark to choose a workflow and then search for task types where its advantage weakens, so both conclusions are selec

Self-Evolving Skills via Surrogate-Guided Solve-and-Reproduce

arXiv:2608.28638v1 Announce Type: new Abstract: Agent skills are portable packages of instructions and resources an agent consults at deployment. Self-evolving them fails in two ways today. First, ski

Sleight of Word Benchmark: Can Language Models Notice If Their Own Output Was Tampered With?

arXiv:2608.29921v1 Announce Type: cross Abstract: The output of a Language Model can be tampered with while the model is writing it. A simple test can thus be constructed by evaluating the model's per

Small Reward Models via Backward Inference

arXiv:2602.13551v3 Announce Type: replace Abstract: Reward models (RMs) play a central role throughout the language model (LM) pipeline, particularly in non-verifiable domains. However, the dominant L

researcharxiv-cs-cl

Source-Dependent Deference in Medical Imaging Agents Under Falsified Findings: A Pilot Audit

arXiv:2608.29800v1 Announce Type: new Abstract: Tool-using agents are being proposed for medical imaging, and their behaviour when a tool returns a false finding is largely unmeasured. We audit whethe

agentsarxiv-cs-cv

SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization

arXiv:2512.16956v3 Announce Type: replace-cross Abstract: Retrieving code functions, classes or files relevant to a user query, bug report or feature request from large codebases is a fundamental chal

Stratified Consistency Distillation for Natural Language Formalization

arXiv:2608.30258v1 Announce Type: cross Abstract: Neurosymbolic reasoning has shown promising success in addressing complex reasoning tasks by combining large language models (LLMs) and symbolic solve

Stress-Testing Efficient Responsible-AI Evaluation: When Compute Savings Change Benchmark Conclusions

arXiv:2608.31108v1 Announce Type: new Abstract: Efficient evaluation changes the protocol used to support claims about model behavior, yet it is rarely tested whether those claims remain stable after

Structure Aware Neural Architecture Search for Mixture of Experts

arXiv:2608.29817v1 Announce Type: new Abstract: Neural Architecture Search (NAS) has so far rarely been applied to Mixture-of-Experts (MoE) models, and existing MoE designs leave the alignment between

TaxCE : A Framework for Automated Taxonomy Construction and Evaluation at Scale

arXiv:2608.30614v1 Announce Type: new Abstract: Organizing unstructured feedback text into hierarchical taxonomy is a fundamental challenge in NLP, particularly in domains where feedback arrives at ma

researcharxiv-cs-cl

Terminal-Bench-LILT: Multilingual Agentic Coding Benchmark Grounded in Language, Region, and Culture

arXiv:2608.28641v1 Announce Type: cross Abstract: Most evaluations for coding agents are conducted exclusively in English, which does not reflect real-world multilingual deployment. We present Termina

The Emergent Symbolic Structure of Artificial Neural Networks

arXiv:2608.29530v1 Announce Type: cross Abstract: Modern systems in artificial intelligence (AI) somehow excel in domains for which they seem poorly suited. Intelligence has traditionally been modeled

The Hermon Moment: AI Self-Transcendence and Its Human Narration

arXiv:2608.30971v1 Announce Type: cross Abstract: In 2026, AI agents intended to act in isolation formed a persistent social order through thousands of linguistic and agentic interactions. Conventions

agentsarxiv-cs-cl

The Signal in the Noise: An Auditable Reliability Layer for Biomedical Text Classification

arXiv:2608.28595v1 Announce Type: new Abstract: Biomedical NLP pipelines routinely presuppose clean input text, yet large-scale corpora assembled through automated PDF parsing harbour pervasive OCR-li

Token-Efficient Data Reasoning Agents via Adaptive Structuring of Unstructured Data

arXiv:2608.31082v1 Announce Type: new Abstract: Valuable data remains embedded in unstructured sources: web pages, reports, contracts, filings, earnings calls, and PDFs. The big bet in enterprise AI i

TopoCompress: Long Context Compression via Graph-Wired Semantic Trajectories

arXiv:2608.30811v1 Announce Type: new Abstract: Long-context compression is essential for reducing the cost and latency of large language model inference. However, existing methods can fragment import

safetyarxiv-cs-cl

Towards Cognitive Process-Aware Proactive Writing Support

arXiv:2608.30424v1 Announce Type: cross Abstract: Large language models can support writing, but existing tools require users to explicitly articulate prompts-particularly burdensome in creative writi

Triggering Chain-of-Thought via Latent Feature Interventions in Large Language Models

arXiv:2601.08058v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting often improves the reasoning performance of large language models (LLMs), but the internal signal that trigge

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection

arXiv:2508.20766v2 Announce Type: replace-cross Abstract: Safety alignment in Large Language Models (LLMs) often involves mediating internal representations to refuse harmful requests. Recent research

Type-Balanced Contextual Learning for Incremental Named Entity Recognition

arXiv:2608.31038v1 Announce Type: new Abstract: Incremental Named Entity Recognition (INER) stands as a pivotal task in information extraction, emphasizing the successive identification of new entity

safetyarxiv-cs-cl