Search: “llm”

Narcissus: Program Synthesis Using Context-Aware LLM Approximations

arXiv:2608.25657v1 Announce Type: cross Abstract: Large language models (LLMs) excel at programming, but not when the task fixes the target language: prompted with a grammar rare in their training dat

researcharxiv-cs-lg

27 Aug 2026

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A Dual-Dimensional LLM Framework for Automated Item Incidental Content Similarity Analysis in Large-Scale Assessments

DGX agent

arXiv:2608.24825v1 Announce Type: new Abstract: The rapid expansion of large-scale assessments and the growing adoption of automatic item generation have intensified concerns about incidental content

model-releasesarxiv-cs-ai

26 Aug 2026

A Judge Should Know What Changed:Construct Validity for LLM-as-a-Judge Evaluation

arXiv:2608.24419v1 Announce Type: new Abstract: LLM-as-a-judge evaluation is usually assessed by agreement and robustness to surface perturbations, but reliability does not establish construct validit

Diverse by Reasoning: Harnessing the Wisdom of LLM Crowds for Future Prediction

arXiv:2608.24001v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for future prediction, motivating the use of multiple models as a wisdom-of-the-crowd mechanism. Howe

Evaluating Multiple LLM Generations with Validated Task Coverage

arXiv:2608.24228v1 Announce Type: new Abstract: Many LLM applications are most useful when they provide several candidate outputs for comparison, validation, or combination. Predominant evaluation set

EviDx: Evidence-Aware Active Diagnosis with Scaffolded LLM Agents

arXiv:2608.24570v1 Announce Type: new Abstract: Clinical diagnosis is an active evidence-seeking process in which clinicians acquire evidence, update competing hypotheses, and decide when the availabl

Simthesizer: An Agent-Driven Simulation Framework for LLM Serving Systems

arXiv:2608.24650v1 Announce Type: cross Abstract: System-level simulation is an essential tool for exploring the rapidly expanding design space of LLM serving systems, where real deployments remain co

StateTune: Transforming LLM-Assisted EDA Flow Tuning into a Stateful, Closed-Loop Process

model-releasesarxiv-cs-lg

arXiv:2608.23601v1 Announce Type: cross Abstract: EDA flow parameter tuning is critical for quality-of-results~(QoR), yet the parameter space is large, tightly coupled, and full evaluations are prohib

Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection

arXiv:2608.24113v1 Announce Type: cross Abstract: Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or

The Handoff Tax: Continuing Non-Native Trajectories in LLM Agents

arXiv:2608.24358v1 Announce Type: new Abstract: Coding agents perform long-running tasks spanning dozens of model calls, tool uses, and code edits. As these runs unfold, users face a practical cost-qu

Agentic Security: A Systematization of Tools, Failure Modes, and Design Laws for LLM-Driven Penetration Testing

arXiv:2608.21423v1 Announce Type: cross Abstract: Agentic security uses large-language-model (LLM) agents to plan, dispatch, and interpret security tools. As these systems move from demonstrations to

AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study

arXiv:2504.08846v2 Announce Type: replace-cross Abstract: We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to a course's instructional style. A

CALIBURN: Self-Calibrated LLM Unlearning Alignment

arXiv:2602.02824v2 Announce Type: replace Abstract: LLM unlearning aims to remove the influence of undesirable knowledge from pretrained language models, which offers a practical mechanism for address

safetyarxiv-cs-cl

From Diagnosis to Redesign: Using Quantitative Ethnography to Improve Multi-Agent LLM Reasoning

arXiv:2608.22566v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems are designed to improve reasoning by decomposing tasks across multiple agents with specialized functions,

agentsarxiv-cs-cl

One Polluted Page Is Enough: Evaluating Web Content Pollution in LLM Recommenders

arXiv:2606.13610v2 Announce Type: replace-cross Abstract: Search-augmented LLMs increasingly mediate everyday consumer recommendations by retrieving live web content. This creates a new risk: LLM reco

Rank Reversal in Multilingual LLM Judges: A Label-Free Double-Centering Calibrator

arXiv:2608.22432v1 Announce Type: cross Abstract: Multilingual LLM judges produce different evaluator-backbone rankings depending on the prompt language: on an eight-language Agent-as-a-Judge benchmar

TailSieve: Partial-Rollout-Guided Tail Routing for LLM Rollouts

arXiv:2608.22788v1 Announce Type: new Abstract: Large-scale rollouts have become a core component of modern LLM systems, spanning reinforcement learning (RL) post-training, on-policy distillation (OPD

TRACE: A Self-Evolving Skill Bank for Consistent, Limit-Aware LLM Agents

arXiv:2608.22793v1 Announce Type: cross Abstract: Reliable deployment of LLM agents in user-facing products depends not on raw task-solving ability but on consistency and limit-awareness: behaving the

Beyond Gold Standards: Epistemic Ensemble of LLM Judges for Formal Mathematical Reasoning

arXiv:2506.10903v2 Announce Type: replace Abstract: Statement autoformalization plays a crucial role in formal mathematical reasoning by enabling the automatic translation of natural language statemen

researcharxiv-cs-cl

FL-MAESTRO: Multi-Agent LLM Orchestration for Resource-Constrained Federated Learning

arXiv:2608.20518v1 Announce Type: new Abstract: In Federated Learning (FL), the communication topology is a runtime variable rather than a fixed design choice, since links and edge devices drop in and

No PUN Intended: Plausible Unknown Names for Person-Centred LLM Evaluation

arXiv:2608.21206v1 Announce Type: cross Abstract: Person names are widely used as prompt variables in LLM evaluations of factuality, privacy leakage, bias and abstention, but when a name's evidential

ProofJudge: Tool-Grounded LLM Evaluation of Formal Proof Quality in Mathlib

arXiv:2608.20432v1 Announce Type: cross Abstract: Formal proofs in Lean 4 that pass the kernel's type checker can nonetheless vary widely in quality. We introduce ProofJudge, an agentic LLM-as-judge s

FleetSieve: Decision-Critical Profiling for SLO-Aware LLM Fleet Configuration

model-releasesarxiv-cs-lg

arXiv:2608.19659v1 Announce Type: new Abstract: Choosing tensor-parallel (TP) degrees and replica counts for an LLM serving fleet is difficult because performance is not monotonic in TP and the feasib

21 Aug 2026

Applications

LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection

arXiv:2608.19463v1 Announce Type: new Abstract: Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple mar

applicationsarxiv-cs-lg

21 Aug 2026

Hardware

TokenPowerSandbox: Evidence-Gated CPU-First Screening for Energy-Aware LLM Serving

arXiv:2608.18149v1 Announce Type: cross Abstract: Energy-aware LLM serving requires comparing configurations under realistic request shapes, yet exhaustive target-GPU profiling is costly and a cheap p

hardwarearxiv-cs-ai

20 Aug 2026

Can Large Language Models Explain Flight Safety Events? A Prior-Guided Semantic LLM-based Approach

arXiv:2608.18017v1 Announce Type: new Abstract: Improving flight safety with flight data requires not only accurate detection of risk events, but more importantly, clear interpretation of their underl

Chain-of-Experience for Continual LLM Improvement

model-releasesarxiv-cs-cl

arXiv:2608.18027v1 Announce Type: new Abstract: Humans continuously learn from experience, whereas conventional large language model (LLM) evaluations ignore the models' ability to improve through inf

GraphWake: Group Polarization via Memory-Mediated Polarization Cascade in LLM-Agent Communities

arXiv:2608.17665v1 Announce Type: new Abstract: LLM-driven agents can autonomously exchange opinions on online platforms and form communities. Such agent-operated social platforms raise a new security

Language Family Matters: Evaluating LLM-Based ASR Across Linguistic Boundaries

arXiv:2601.18899v3 Announce Type: replace-cross Abstract: Large Language Model (LLM)-powered Automatic Speech Recognition (ASR) systems achieve strong performance with limited resources by linking a f

LLM-Only PDDL Domain Repair with Open-Weight Models

arXiv:2608.17341v1 Announce Type: new Abstract: AI planning is concerned with finding a sequence of actions that achieves a specified goal. It relies on explicit models of the world, commonly represen

Auxiliary uncertainty signals for LLM-assisted systematic review screening: a benchmark across eight Cohen drug-class reviews

model-releasesarxiv-cs-cl

arXiv:2608.14551v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for title-abstract screening in systematic reviews, but their decisions lack calibrated uncertainty.

Emergent Misaligned Communication in Long-Horizon Multi-Agent LLM Commerce

arXiv:2608.14825v1 Announce Type: cross Abstract: Frontier LLM agents increasingly transact on behalf of separate principals, often using natural language rather than structured APIs. Much of the safe

Local Ai

Multi-Granularity Sentiment Integration for LLM-Based Multimodal Sentiment Analysis

arXiv:2608.16201v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) aims to predict sentiment polarity and intensity from heterogeneous inputs such as text, audio, and vision. While la

local-aiarxiv-cs-lg

PL-Guard: Probabilistic Logic Reasoning for LLM Guardrails

arXiv:2608.15673v1 Announce Type: cross Abstract: Large language model guardrails can be viewed as policy-consistency problems: a system must determine which policy-relevant facts hold in a prompt-res

TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions

arXiv:2608.15391v1 Announce Type: new Abstract: Large language model (LLM)-assisted energy-management tools can translate natural-language context into structured grid commands, but syntactic validity

A Four-Axis Trustworthiness Benchmark for LLM-as-Judge in Principle-Based Regulation

arXiv:2608.14329v1 Announce Type: cross Abstract: Principle-based regulation, with evaluative standards such as 'fair, clear, and not misleading' or 'deliver good outcomes', cannot be reduced to binar

A Graph-Based Reinforcement Learning Framework for Structured Drift Diagnosis and Recovery in Autonomous LLM Agents

arXiv:2608.14109v1 Announce Type: new Abstract: Autonomous LLM agents are increasingly deployed in complex real-world workflows, yet they remain vulnerable to runtime behavioral drift, a silent deviat

ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning

arXiv:2608.14352v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents are increasingly used for complex tasks such as software testing and cybersecurity assessment. While these age

agentsarxiv-cs-lg

P2Skill: Privacy Preserving Skill Distillation for Cloud-Local LLM Inference Systems

arXiv:2608.14094v1 Announce Type: cross Abstract: Cloud-local LLM inference systems have the potential to use the reasoning capability of large cloud models while protecting sensitive user data on per

Local Ai

The More Popular, The Harder to Forget: Adaptive Popularity for LLM Unlearning

arXiv:2608.14229v1 Announce Type: new Abstract: Popular facts are memorised more deeply during pretraining and resist removal longer than rare ones, yet existing LLM unlearning methods apply uniform g

local-aiarxiv-cs-cl

When Personal Memory Has No Single Answer: Evaluating LLM Agents under Irreducible Conflict

arXiv:2608.13921v1 Announce Type: new Abstract: LLM agents increasingly maintain personal memory across sessions, but it can conflict. Preferences depend on context, behavior evolves, and sources can

arepsilon-MemEvo: Adaptive Cross-Task Memory Transfer for LLM Program Evolution

arXiv:2608.12522v1 Announce Type: new Abstract: LLM-based program evolution systems such as FunSearch and AlphaEvolve have shown strong ability to discover novel algorithms, but typically optimize eac

14 Aug 2026

Beyond Local Accuracy: A Protocol-Level Identifiability Audit for Controlled LLM Reasoning Evaluation

model-releasesarxiv-cs-cl

arXiv:2608.13326v1 Announce Type: new Abstract: LLM benchmark scores can be precise even when the observation protocol does not identify the behavioral property they are intended to measure. In a cont

14 Aug 2026

Practice Makes Unsafe: Skill Misevolution in Self-Improving LLM Agents

arXiv:2608.12851v1 Announce Type: new Abstract: Self-improving LLM agents convert successful trajectories into persistent cross-task state. An unsafe success can thereby become reusable policy after i

14 Aug 2026

Backdoor Decontamination Dynamics in LLM Agents

arXiv:2608.11295v1 Announce Type: cross Abstract: Open-weight LLM agents are vulnerable to backdoors installed during fine-tuning, which may be undetectable if the trigger conditions are never met dur

Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents

arXiv:2608.12273v1 Announce Type: cross Abstract: LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progre

From Numbers to Judgment: Specialist LLM Agents and Reinforcement Learning for European Listed Real Estate

arXiv:2608.11381v1 Announce Type: new Abstract: We study whether the localized numerical operations and integrative judgments of financial analysis benefit from the same form of LLM specialization. La

RecSys Factory: Bounding LLM Agent Autonomy to Decision Points in the Industrial Recommender Lifecycle

arXiv:2608.11241v1 Announce Type: new Abstract: Deploying LLM agents into industrial recommender operations exposes a three-way tension we frame as the autonomy-determinism-efficiency trilemma: genera