Search: “llm”

SWE-Proof: Can Language Models Resolve Real-World Issues with Machine-Checked Proofs?

arXiv:2609.21190v1 Announce Type: cross Abstract: Ensuring the correctness of LLM-generated code is a core challenge for modern software engineering. Benchmarks for agentic code generation check corre

21 Sept 2026

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Verify, Don't Trust: Agentic Model Development for Video Discovery Retrieval at Scale

DGX agent

arXiv:2609.21257v1 Announce Type: cross Abstract: Large language model (LLM) agents can propose, implement, and evaluate model changes. Autoresearch loops demonstrate this capability through minutes-s

hardwarearxiv-cs-ai

21 Sept 2026

AdaRepair-Mem: Adaptive Experience Orchestration for Repository-Level Program Repair

arXiv:2609.20130v1 Announce Type: cross Abstract: Recent memory-augmented repository-level program repair methods reuse historical repair experiences to improve LLM-based issue resolution. However, ou

AutoData: Agentic Search for Pre-training Data Selection

arXiv:2609.19754v1 Announce Type: new Abstract: LLM agents have recently shown promise in automating machine learning engineering by editing model and training code under execution feedback. Data, how

Deep Noir: Autonomous Steering Discovery via Architectural Chronometry in Transformer Models

arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a f

DeliveryGym: An RL Environment for Long-Horizon Embodied Agent Planning with Adaptive Curriculum

arXiv:2609.19801v1 Announce Type: new Abstract: Executable environments enable LLM agents to learn from the consequences of their actions. For embodied agents, those consequences extend beyond whether

safetyarxiv-cs-lg

Faithful, Not Corrective: Model Capability Governs Message-Format Effects in Multi-Hop Agent Relays

arXiv:2607.09678v2 Announce Type: replace Abstract: When LLM agents hand information to one another, does the message format matter? Two literatures disagree: format-optimization work reports that str

MTVA-Bench: Evaluating the Language Model Inside Cascaded Voice Agents

arXiv:2609.20152v1 Announce Type: new Abstract: Generally, most voice agents are cascaded systems, i.e., an ASR model transcribes the caller's audio, a language model reads the transcript and decides

PAPC: Platform Mediation for Privacy-Propagation Externalities in AI-Mediated Workflows

arXiv:2609.19226v1 Announce Type: cross Abstract: AI-mediated platforms coordinate work through LLM agents acting for different principals. In these workflows, privacy loss can be created before a fin

safetyarxiv-cs-ai

Reflective Recovery: A Self-Supervised Method for Reasoning by Learning from Mistakes

arXiv:2609.19156v1 Announce Type: new Abstract: Data-driven fine-tuning is widely adopted to enhance reasoning in Large Language Models (LLMs) due to its simplicity and efficiency. However, mainstream

Self-Evolving Search Index

arXiv:2609.19656v1 Announce Type: cross Abstract: Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an

Social Simulacra in the Wild: AI Agent Communities on Moltbook

arXiv:2603.16128v3 Announce Type: replace Abstract: As autonomous LLM-based agents increasingly populate social platforms, understanding the dynamics of AI-agent communities becomes essential for both

agentsarxiv-cs-cl

Watermarking Diffusion Language Models

arXiv:2509.24368v3 Announce Type: replace-cross Abstract: We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary

A Study of the Reliability of Agentic AI-Generated Programs

arXiv:2609.18298v1 Announce Type: cross Abstract: Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code.

Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking

arXiv:2609.18909v1 Announce Type: cross Abstract: Agent benchmarks are substantially more costly to evaluate than conventional LLM benchmarks. Benchmark compression is therefore a natural solution, ye

Cultural Competence in Context: A Large Language Model Passes the Turing Test in Finland

arXiv:2609.18394v1 Announce Type: new Abstract: We report the results of a Turing Test conducted in Finland in the Finnish language. Because languages and cultural contexts are unevenly represented in

Disentangling Long-Term Memory via Latent Neuro-Symbolic Reasoning

arXiv:2609.18461v1 Announce Type: new Abstract: Personalized agents are required to reason over long-term history interactions to infer both explicit preferences and implicit behavioral evidence. Whil

English Word Sense Disambiguation in 2026: When the Labels Become the Bottleneck

arXiv:2609.17554v1 Announce Type: new Abstract: In English all-words word sense disambiguation (WSD), the labels, not the models, have become the bottleneck: frontier LLMs are accurate enough that the

EviGen: Predictive Evidence Scaffolding for Verifiable Clinical Rationale Generation

arXiv:2609.18852v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) capture years of patient history across notes, codes, labs, and procedures, and contain evidence needed to

Tutorials

Fallacy Benchmarks Measure Scheme Recognition, Not Fallacy Detection

arXiv:2609.18644v1 Announce Type: new Abstract: Fallacy-detection benchmarks pair fallacy classes with a single 'valid' or 'none' class that takes everything data collection did not label as a fallacy

tutorialsarxiv-cs-cl

Rethinking Critic Learning in PPO: Understanding and Mitigating Value Flattening

arXiv:2609.18708v1 Announce Type: cross Abstract: In reinforcement learning for large language models, Proximal Policy Optimization (PPO) commonly uses a critic to estimate state values and reduce the

safetyarxiv-cs-ai

Local Ai

TalkMatrix: Generating Character Dialogue that is Both Consistent and Diverse

arXiv:2609.19022v1 Announce Type: cross Abstract: Candidate-based decoding typically selects a completion for each prompt independently, but many applications require a collection of outputs that sati

local-aiarxiv-cs-ai

Hardware

WFM: Wiki Foundation Model for Complex Agentic Reasoning

arXiv:2609.18182v1 Announce Type: new Abstract: Real-world agents fundamentally require persistent non-parametric knowledge for dynamic reasoning, i.e., long-term memory and retrieval-augmented genera

hardwarearxiv-cs-ai

What Counts as Strategic Reasoning? A Systematic Mapping of Chess Research on Humans, Engines, and Language Models

arXiv:2609.18286v1 Announce Type: new Abstract: Chess has long served as a model domain for studying search, expertise, decision-making, and artificial intelligence. The emergence of large language mo

When Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generation

arXiv:2609.18099v1 Announce Type: new Abstract: Graph-based retrieval-augmented generation (RAG) can help answer questions that require information from many documents. However, building a graph often

Are We Grading Properly? Understanding Failure Modes in Medical Benchmarks

arXiv:2609.16023v1 Announce Type: new Abstract: Medical evaluation is shifting from static option-based questioning to realistic clinical scenarios with open-ended output modes. Grading these at scale

BLINDSPOT: A Benchmark for Safety and Refusal Calibration in Long-Horizon Tool-Using Agents

arXiv:2609.16305v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over long-horizon interactions involving tool use, persistent state, evolving authorization, and

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st

Challenges of Auditing: Variability in Outputs of Large Language Models for Health

arXiv:2609.16590v1 Announce Type: new Abstract: People increasingly use frontier AI models for health advice, but via different access modes (e.g., ChatGPT, ChatGPT Health, APIs) with varying settings

Decomposition Buys Integrity, Not Yield

arXiv:2609.17464v1 Announce Type: cross Abstract: Multi-agent systems split a task across a tree of agents and justify the split with folklore: smaller contexts, cleaner separation, parallelism. We as

Hardware

FlashVector: Agent for Hierarchical Model Serving Stack Optimization

arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera

hardwarearxiv-cs-ai

Models as Governed Interfaces for AI-Native MBSE: Read-Side Adequacy and Write-Side Admissibility

arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition

Neuro-Symbolic Synergy for World Modeling

arXiv:2602.10480v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general-purpose reasoning capabilities, yet they frequently hallucinate when used as world models (WMs),

agentsarxiv-cs-cl

Optimal Model Activation Policies for Inference Networks of Large Language Models

arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost

safetyarxiv-cs-cl

RAG-CT: Mitigating Privacy Risks on Retrieval-Augmented Generation Systems via Scanning Prompt Distribution

arXiv:2609.16095v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for improving the quality of generated contents of Large Language Models (LLMs

Local Ai

RepoAtlas: Guiding Coding Agents via Evolving Multimodal Repository Views

arXiv:2609.16936v1 Announce Type: cross Abstract: Large language model (LLM)-powered coding agents have made rapid progress in automating software engineering tasks, yet repository-level issue resolut

local-aiarxiv-cs-ai

RoleBreak: Benchmarking Long-Horizon Role-Playing Robustness in Spoken Dialogue

arXiv:2609.16614v1 Announce Type: cross Abstract: Speech-to-speech dialogue models increasingly support persona control, yet existing spoken role-playing benchmarks remain largely character-centric an

Test-Time Unlearning via Sparse Autoencoder

arXiv:2609.16229v1 Announce Type: cross Abstract: Machine unlearning aims to remove specific knowledge from a trained large language model (LLM) without retraining from scratch. Existing methods modif

Towards Detecting AI-Assisted Responses in Online Surveys

arXiv:2609.17317v1 Announce Type: new Abstract: The use of LLMs to complete online surveys impacts the validity of survey-based research, but detecting such usage remains underexplored. We introduce a

You Don't Need To Train: Agentic Heuristic Learning Studio for Executable Human Activity Recognition

arXiv:2609.16065v1 Announce Type: cross Abstract: Human activity recognition (HAR) is usually framed as gradient-based training of neural networks. Agentic Heuristic Learning (AHL) Studio explores a c

Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study

arXiv:2609.14236v1 Announce Type: cross Abstract: With the rapid proliferation of large language model (LLM)-based systems, AI companions have emerged as conversational agents designed to cultivate em

AttnFuse: A Composable DSL for Compiling Attentions to Fused GPU Kernels

model-releasesarxiv-cs-lg

arXiv:2609.13612v1 Announce Type: new Abstract: Modern AI systems are built on the Transformer architecture, whose core operation, attention, accounts for the majority of computation and memory cost.

BusMA: A Bus Communication Substrate for Multi-Agent Systems

arXiv:2609.15054v1 Announce Type: new Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Exi

Calibrating Interpretability Instruments Before Trusting Their Verdicts

arXiv:2609.14754v1 Announce Type: cross Abstract: Causal claims about large language model (LLM) internals rest on measurements. Those might include a projection, a cosine, an ablation delta, or an in

Can We Trust the Judges? Validation of Factuality Evaluation Methods via Answer Perturbation

arXiv:2609.15561v1 Announce Type: new Abstract: Evaluating the factual correctness of large language models (LLMs) is vital for many applications. But are our evaluation tools themselves trustworthy?

Carryover Drafting: Recycling Rejected States for Speculative Decoding

arXiv:2609.14717v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by verifying multiple drafted tokens in parallel, allowing a single target forward pass to accept sever

CLEAR: Context Augmentation from Contrastive Learning of Experience via Agentic Reflection

arXiv:2604.07487v2 Announce Type: replace Abstract: Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineeri

Data Security in Large Language Models: Risks, Defense, and Directions

arXiv:2508.02312v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine t