Search: “llm”

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization

arXiv:2601.09448v3 Announce Type: replace-cross Abstract: Conventional audio equalization is a static process that requires manual and cumbersome adjustments to adapt to changing listening contexts (e

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Agents

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations

DGX agent

arXiv:2607.04235v1 Announce Type: new Abstract: Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address th

agentsarxiv-cs-cl

7 Jul 2026

Applications

SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks

arXiv:2603.10002v2 Announce Type: replace-cross Abstract: We consider the task of end-to-end spreadsheet generation, where language models produce spreadsheet artifacts to satisfy users' explicit and

applicationsarxiv-cs-ai

The Language of Bargaining: Linguistic Effects in LLM Negotiations

arXiv:2601.04387v2 Announce Type: replace Abstract: Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work

ToolFailBench: Diagnosing Tool-Use Failures in LLM Agents

arXiv:2607.04686v1 Announce Type: cross Abstract: Tool calling is central to modern language model agents, but aggregate benchmark scores often hide where tool use fails. A model that never calls a ne

ViPo-MLLM: Visual-Pose Multimodal LLM for Gloss-Free Sign Language Translation

arXiv:2607.03657v1 Announce Type: cross Abstract: Gloss-free Sign Language Translation (SLT) translates sign language videos into spoken-language sentences without gloss annotations, avoiding costly l

Ask the Right Comparison:Bias-Aware Bayesian Active Top-k Ranking with LLM Judges

model-releasesarxiv-cs-lg

arXiv:2607.02104v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as cheap, scalable judges that compare candidate outputs pairwise -- to rank responses, select models

BOUNDARY_SYNC: Measuring Communication-Induced Representational Coupling in Multi-Agent LLM Systems

arXiv:2607.01600v1 Announce Type: cross Abstract: As large language models (LLMs) are deployed as communicating agents, does inter-agent communication cause outputs to converge? We introduce BOUNDARY_

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training

arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Lar

Gravity-Awareness: Deep Learning Models and LLM Simulation of Human Awareness in Altered Gravity

arXiv:2511.05536v2 Announce Type: replace-cross Abstract: Earth s gravity fundamentally shapes human behaviour. The brain encodes this force as an internal model of gravity, enabling the prediction an

Object Aligner: A Configurable JSON Schema Similarity Score for Graphs, Applied to LLM Prompt Optimization

arXiv:2607.01972v1 Announce Type: cross Abstract: Large language models (LLMs) are often asked to produce JSON conforming to a fixed schema, powering information extraction, tool calling, agentic plan

safetyarxiv-cs-ai

ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning

arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Althou

Local Ai

Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

arXiv:2511.10687v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled w

local-aiarxiv-cs-ai

Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation

arXiv:2607.00454v1 Announce Type: new Abstract: Agricultural advisory systems face a fundamental tension: static agronomic guidelines offer consistent, evidence-based recommendations, yet remain blind

From Holistic Evaluation to Structured Criteria: Rubrics Across the Evolving LLM Landscape

arXiv:2606.08625v2 Announce Type: replace Abstract: As Large Language Models (LLMs) advance toward open-ended autonomous agents, the mechanisms used to evaluate and guide their behavior must evolve ac

safetyarxiv-cs-cl

From Signals to Structure: How Memory Architecture Drives Language Emergence in LLM Agents

arXiv:2607.00233v1 Announce Type: new Abstract: How do two agents invent a shared language from scratch? In a Lewis signaling game, a sender and receiver must coordinate on a code using only their int

LLM-Guided ODE Discovery and Parameter Inference from Small-Cohort Aggregate Data

arXiv:2607.00733v1 Announce Type: cross Abstract: Mechanistic modeling via ordinary differential equations (ODEs) provides interpretable descriptions of complex dynamics and enables inference of under

NeuroFilter: Activation-Based Guardrails for Privacy-Conscious LLM Agents

arXiv:2601.14660v2 Announce Type: replace-cross Abstract: Agentic Large Language Models (LLMs) are models able to reason, plan, and execute tools over unstructured data. These abilities are enabling t

Embodied CAD: Solver-Grounded LLM Agents for Parametric B-Rep Assembly Modeling

arXiv:2606.31252v1 Announce Type: new Abstract: Large language models can write plausible CAD scripts, but reliable industrial CAD modeling requires more than syntactically valid code: every feature,

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression

arXiv:2601.08187v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated promising capabilities in Text-Attributed Graph (TAG) understanding. Recent studies typically focus o

On the Convergence of Self-Improving Online LLM Alignment

arXiv:2606.31524v1 Announce Type: cross Abstract: The Self-Improving Alignment (SAIL) algorithm addresses distribution shift by reducing a bilevel formulation of the problem to an efficient, single-le

Hardware

SeKV: Resolution-Adaptive KV Cache with Hierarchical Semantic Memory for Long-Context LLM Inference

arXiv:2606.31145v1 Announce Type: new Abstract: Large language models increasingly operate over long contexts, where the KV cache becomes a dominant memory bottleneck: its size grows linearly with seq

hardwarearxiv-cs-cl

Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical Fallacies

arXiv:2606.31039v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong semantic capabilities, yet their resilience to manipulative linguistic patterns such as logical fallacies re

5ting at SemEval-2026 Task 8: Strong End-to-End Multi-Turn RAG via LLM-Based Reranking and Faithfulness Control

arXiv:2606.28737v1 Announce Type: cross Abstract: We introduce 5ting, our system for the SemEval2026 Task 8 (MTRAGEval), which evaluates multi-turn Retrieval Augmented Generation (RAG) systems. Multi

Beyond the Mean: Three-Axis Fidelity for Aligning LLM-Based Survey Simulators from Small Pilot Data

arXiv:2606.28963v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate social survey responses, yet their outputs exhibit systematic biases: marginal distributi

Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch

arXiv:2606.28815v1 Announce Type: cross Abstract: Mathswitch is an open-source project that imports mathematical concept records from sources such as Wikidata, Wikipedia, MathWorld, Encyclopedia of Ma

safetyarxiv-cs-ai

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM

arXiv:2606.29563v1 Announce Type: cross Abstract: Large language models (LLMs) excel at complex tasks like question answering and summarization, thanks to their ability to handle long-context inputs.

Evidence-Driven LLM Agent for C-to-Synthesizable-C Conversion and Verification

arXiv:2606.28409v1 Announce Type: cross Abstract: Software-compilable C programs routinely fail to complete the four-stage pipeline of a high-level synthesis (HLS) toolchain -- compilation, C simulati

Applications

Exploring the Value of Diverse LLM Explanations in Introductory Programming

arXiv:2606.28882v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown the potential to generate code explanations that surpass those of peers in quality, offering promising opportu

applicationsarxiv-cs-ai

HEARTS: Benchmarking LLM Reasoning on Health Time Series

arXiv:2603.06638v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing be

How much of an LLM-generated clinical corpus is actually new? A production-scale measurement of content redundancy for provenance classification

arXiv:2606.29605v1 Announce Type: new Abstract: Clinical machine learning increasingly relies on training corpora generated by large language models (LLMs) rather than annotated by clinicians, and suc

Local Ai

How to Leverage Synthetic Speech for LLM-Based ASR Systems?

arXiv:2606.29031v1 Announce Type: cross Abstract: In regulated domains such as banking and healthcare, where privacy constraints make real speech costly to collect and retain, synthetic speech from mo

local-aiarxiv-cs-ai

LLM-Guided Planning for Multi-hop Reasoning over Multimodal Nuclear Regulatory Documents

arXiv:2606.29399v1 Announce Type: new Abstract: Reviewing nuclear regulatory documents requires multi-hop reasoning across tens of thousands of pages, where judgments depend on evidence assembled acro

Local Ai

LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution

arXiv:2606.28335v1 Announce Type: cross Abstract: We argue, with systematic empirical evidence, that a large language model's political ideology is not a fixed point, but a conditional distribution P(

local-aiarxiv-cs-ai

LLM Semantic Signaling Game and Mechanism Design: Systematic Blindness, Awareness Shaping, and Mindset Dynamics

arXiv:2606.29113v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate strategic interactions through natural language, making semantic control a critical element of commu

safetyarxiv-cs-ai

Not-quite-human tastes: the stylized omnivorousness of LLM survey surrogates

arXiv:2606.30085v1 Announce Type: new Abstract: Large-language models have proven to be remarkable if inconsistent parrots of public attitudes and opinions. The extent to which LLMs are able to produc

Optimizing Expert-Designed Crystal Graph Networks for Band-Gap Prediction with an Autonomous LLM Research Loop

arXiv:2606.29717v1 Announce Type: cross Abstract: Predicting a material's properties from its structure is a central, fast-advancing problem in computational materials science. A decade of work has pr

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation

arXiv:2602.09305v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate transformative potential, yet their reasoning remains inconsistent and unreliable. Reinforcement learning (

safetyarxiv-cs-lg

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs

arXiv:2511.10480v3 Announce Type: replace-cross Abstract: Optimizing the performance of large language models (LLMs) on large-scale AI training and inference systems requires a scalable and expressive

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives

arXiv:2510.06096v3 Announce Type: replace-cross Abstract: The objectives that Large Language Models (LLMs) implicitly optimize remain dangerously opaque, making trustworthy alignment and auditing a gr

safetyarxiv-cs-cl

The Effect of Scripts and Formats on LLM Numeracy

arXiv:2601.15251v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive proficiency in basic arithmetic, rivaling human-level performance on standard numerical tasks.

researcharxiv-cs-cl

TraceLab: Characterizing Coding Agent Workloads for LLM Serving

arXiv:2606.30560v1 Announce Type: cross Abstract: Coding agents are rapidly becoming a major application of agentic LLMs, but serving them efficiently remains challenging. Progress on this challenge r

When Can Conformal Risk Control Certify LLM Outputs? Bounds, Impossibility, and Adaptation for Structured Generation

arXiv:2606.29054v1 Announce Type: new Abstract: Large language models (LLMs) deployed for structured generation (NER, JSON extraction, QA, and classification) lack formal reliability guarantees, and s

researcharxiv-cs-lg

When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis

arXiv:2606.29251v1 Announce Type: new Abstract: Financial decision-makers face more information than they can directly inspect, making context compression necessary. Yet when large language models (LL

Tutorials

CBD: API-Only LLM Black-Box Unlearning through Controlled Behavioral Divergence

arXiv:2606.27683v1 Announce Type: cross Abstract: Edge devices increasingly invoke large language models (LLMs) through API services for context aware edge intelligence, while edge generated data may

tutorialsarxiv-cs-ai

Contagion Networks: Evaluator Preference Propagation in Multi-Agent LLM Systems

arXiv:2606.20493v2 Announce Type: replace-cross Abstract: When large language models serve as evaluators in multi-agent systems, their strategy preferences -- whether induced by explicit prompts or by

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

arXiv:2504.16116v4 Announce Type: replace-cross Abstract: The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software v

End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference

arXiv:2606.27743v1 Announce Type: cross Abstract: Large Language Models (LLMs) inference is typically deployed under a static resource assumption, where models execute a fixed computational graph rega