Search: “llm”

MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety

arXiv:2605.01687v1 Announce Type: new Abstract: We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic

5 May 2026

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Watermarking LLM Agent Trajectories

DGX agent

arXiv:2602.18700v2 Announce Type: replace-cross Abstract: LLM agents rely heavily on high-quality trajectory data to guide their problem-solving behaviors, yet producing such data requires substantial

model-releasesarxiv-cs-cl

5 May 2026

ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering

arXiv:2505.23723v2 Announce Type: replace Abstract: The emergence of large language model (LLM)-based agents has significantly advanced the development of autonomous machine learning (ML) engineering.

4 May 2026

LLMs Capture Emotion Labels, Not Emotion Uncertainty: Distributional Analysis and Calibration of Human--LLM Judgment Gaps

arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i

1 May 2026

Analytica: Soft Propositional Reasoning for Robust and Scalable LLM-Driven Analysis

arXiv:2604.23072v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly tasked with complex real-world analysis (e.g., in financial forecasting, scientific discovery), yet t

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines

arXiv:2604.23178v1 Announce Type: new Abstract: LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluati

Revisable by Design: A Theory of Streaming LLM Agent Execution

arXiv:2604.23283v1 Announce Type: new Abstract: Current LLM agents operate under an implicit but universal assumption: execution is a transaction -- the user submits a request, the agent works in isol

agentsarxiv-cs-lg

Uncertainty Propagation in LLM-Based Systems

arXiv:2604.23505v1 Announce Type: cross Abstract: Uncertainty in large language model (LLM)-based systems is often studied at the level of a single model output, yet deployed LLM applications are comp

researcharxiv-cs-ai

Do LLM Decoders Listen Fairly? Benchmarking How Language Model Priors Shape Bias in Speech Recognition

arXiv:2604.21276v1 Announce Type: cross Abstract: As pretrained large language models replace task-specific decoders in speech recognition, a critical question arises: do their text-derived priors mak

24 Apr 2026

ActuBench: A Multi-Agent LLM Pipeline for Generation and Evaluation of Actuarial Reasoning Tasks

arXiv:2604.20273v1 Announce Type: new Abstract: We present ActuBench, a multi-agent LLM pipeline for the automated generation and evaluation of advanced actuarial assessment items aligned with the Int

Bias in the Tails: How Name-conditioned Evaluative Framing in Resume Summaries Destabilizes LLM-based Hiring

arXiv:2604.19984v1 Announce Type: cross Abstract: Research has documented LLMs' name-based bias in hiring and salary recommendations. In this paper, we instead consider a setting where LLMs generate c

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

LLM-guided phase diagram construction through high-throughput experimentation

arXiv:2604.20304v1 Announce Type: cross Abstract: Constructing phase diagrams for multicomponent alloys requires extensive experimental measurements and is a time-consuming task. Here we investigate w

LLM StructCore: Schema-Guided Reasoning Condensation and Deterministic Compilation

arXiv:2604.20560v1 Announce Type: new Abstract: Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of f

Separable Pathways for Causal Reasoning: How Architectural Scaffolding Enables Hypothesis-Space Restructuring in LLM Agents

arXiv:2604.20039v1 Announce Type: new Abstract: Causal discovery through experimentation and intervention is fundamental to robust problem solving. It requires not just updating beliefs within a fixed

researcharxiv-cs-ai

Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems

arXiv:2604.19540v1 Announce Type: cross Abstract: Teams of LLM agents increasingly collaborate on tasks spanning days or weeks: multi-day data-generation sprints where generator, reviewer, and auditor

22 Apr 2026

Applications

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption

arXiv:2510.18333v2 Announce Type: replace-cross Abstract: Despite progress in watermarking algorithms for large language models (LLMs), real-world deployment remains limited. We argue that this gap st

applicationsarxiv-cs-cl

22 Apr 2026

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring

arXiv:2604.18835v1 Announce Type: cross Abstract: We propose a scalable, multifactorial experimental framework that systematically probes LLM sensitivity to subtle semantic changes in pairwise documen

22 Apr 2026

Clinical Note Bloat Reduction for Efficient LLM Use

arXiv:2604.16364v1 Announce Type: cross Abstract: Health systems are rapidly deploying large language models (LLMs) that use clinical notes for clinical decision support applications. However, modern

21 Apr 2026

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning

arXiv:2510.00761v5 Announce Type: replace Abstract: Large language model (LLM) unlearning aims to surgically remove the influence of undesired data or knowledge from an existing model while preserving

safetyarxiv-cs-lg

21 Apr 2026

LLM-AUG: Robust Wireless Data Augmentation with In-Context Learning in Large Language Models

arXiv:2604.17770v1 Announce Type: new Abstract: Data scarcity remains a fundamental bottleneck in applying deep learning to wireless communication problems, particularly in scenarios where collecting

researcharxiv-cs-lg

21 Apr 2026

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization

arXiv:2601.20868v2 Announce Type: replace Abstract: Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on man

researcharxiv-cs-lg

17 Apr 2026

The Autocorrelation Blind Spot: Why 42% of Turn-Level Findings in LLM Conversation Analysis May Be Spurious

arXiv:2604.14414v1 Announce Type: new Abstract: Turn-level metrics are widely used to evaluate properties of multi-turn human-LLM conversations, from safety and sycophancy to dialogue quality. However

safetyarxiv-cs-cl

17 Apr 2026

The cognitive companion: a lightweight parallel monitoring architecture for detecting and recovering from reasoning degradation in LLM agents

model-releasesarxiv-cs-lg

arXiv:2604.13759v1 Announce Type: cross Abstract: Large language model (LLM) agents on multi-step tasks suffer reasoning degradation, looping, drift, stuck states, at rates up to 30% on hard tasks. Cu

16 Apr 2026

Adaptive Budget Allocation in LLM-Augmented Surveys

arXiv:2604.12497v1 Announce Type: new Abstract: Large language models (LLMs) can generate survey responses at low cost, but their reliability varies substantially across questions and is unknown befor

researcharxiv-cs-lg

Local Ai

GigaCheck: Detecting LLM-generated Content via Object-Centric Span Localization

arXiv:2410.23728v3 Announce Type: replace Abstract: With the increasing quality and spread of LLM assistants, the amount of generated content is growing rapidly. In many cases and tasks, such texts ar

local-aiarxiv-cs-cl

How memory can affect collective and cooperative behaviors in an LLM-Based Social Particle Swarm

arXiv:2604.12250v1 Announce Type: new Abstract: This study examines how model-specific characteristics of Large Language Model (LLM) agents, including internal alignment, shape the effect of memory on

PrivacyReasoner: Can LLM Emulate a Human-like Privacy Mind?

arXiv:2601.09152v2 Announce Type: replace Abstract: Prior work on LLM-based privacy focuses on norm judgment over synthetic vignettes, rather than how people think about a specific data practice and f

Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models

arXiv:2604.10985v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have rapidly advanced by leveraging powerful pre-trained Large Language Models (LLMs) as core reasoning backbones. As new

Local Ai

ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection

arXiv:2604.11790v1 Announce Type: cross Abstract: Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet rem

local-aiarxiv-cs-ai

ConfigSpec: Profiling-Based Configuration Selection for Distributed Edge--Cloud Speculative LLM Serving

arXiv:2604.09722v1 Announce Type: cross Abstract: Speculative decoding enables collaborative Large Language Model (LLM) inference across cloud and edge by separating lightweight token drafting from he

CONSCIENTIA: Can LLM Agents Learn to Strategize? Emergent Deception and Trust in a Multi-Agent NYC Simulation

arXiv:2604.09746v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed as autonomous agents, understanding how strategic behavior emerges in multi-agent environmen

Diagnosing Retrieval vs. Utilization Bottlenecks in LLM Agent Memory

arXiv:2603.02473v2 Announce Type: replace Abstract: Memory-augmented LLM agents store and retrieve information from prior interactions, yet the relative importance of how memories are written versus h

From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution

arXiv:2604.11378v1 Announce Type: new Abstract: The dominant paradigm for building LLM based agents is the Agent Loop, an iterative cycle where a single language model decides what to do next by readi

Local Ai

WebLLM: A High-Performance In-Browser LLM Inference Engine

arXiv:2412.15803v2 Announce Type: replace-cross Abstract: Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-gra

local-aiarxiv-cs-ai

From Paper to Program: Accelerating Quantum Many-Body Algorithm Development via a Multi-Stage LLM-Assisted Workflow

arXiv:2604.04089v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate code rapidly but remain unreliable for scientific algorithms whose correctness depends on structural

13 Apr 2026

Many-Tier Instruction Hierarchy in LLM Agents

arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level

13 Apr 2026

Attention Flows: Tracing LLM Conceptual Engagement via Story Summaries

arXiv:2604.06416v1 Announce Type: cross Abstract: Although LLM context lengths have grown, there is evidence that their ability to integrate information across long-form texts has not kept pace. We ev

Benchmarking LLM Tool-Use in the Wild

arXiv:2604.06185v1 Announce Type: cross Abstract: Fulfilling user needs through Large Language Model multi-turn, multi-step tool-use is rarely a straightforward process. Real user interactions are inh

HCRE: LLM-based Hierarchical Classification for Cross-Document Relation Extraction with a Prediction-then-Verification Strategy

arXiv:2604.07937v1 Announce Type: new Abstract: Cross-document relation extraction (RE) aims to identify relations between the head and tail entities located in different documents. Existing approache

LLM-based Schema-Guided Extraction and Validation of Missing-Person Intelligence from Heterogeneous Data Sources

arXiv:2604.06571v1 Announce Type: cross Abstract: Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative

Believed but Not Said: Measuring Hidden Belief Collapse in Multi-Agent LLM Discussions

arXiv:2610.22138v1 Announce Type: new Abstract: LLM systems increasingly rely on groups of agents that discuss, critique, and check one another, assuming that peers will catch individual errors. We te

FGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization

arXiv:2610.21246v1 Announce Type: new Abstract: Large language model (LLM)-guided Bayesian optimization (BO) uses past observations to guide search, but proposed directions and their revision can rema

Tutorials

L2G-SR: Learning to Guide LLM-based Symbolic Regression

arXiv:2610.20685v1 Announce Type: new Abstract: Symbolic regression searches for an equation that explains observed data. Numerical error is commonly used to guide the search, but it alone can favor a

tutorialsarxiv-cs-ai

Applications

Self-Guided LLM Reasoning for Error Diagnosis in Vehicle Routing Problems

arXiv:2610.21393v1 Announce Type: new Abstract: Vehicle Routing Problems (VRPs) are fundamental to many real-world applications. Recent advances in large language models (LLMs) have spurred progress i

applicationsarxiv-cs-ai

When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles

arXiv:2610.21139v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values. Yet

BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems

arXiv:2610.18780v1 Announce Type: new Abstract: Large language model multi-agent systems extend individual agents' capabilities through collaboration across specialized roles, tools, and workflows. Ye

15 Oct 2026

DUALVIEW: Leveraging Broad and Output-Specific Evidence for LLM-based Multi-Output Text Regression

arXiv:2610.19206v1 Announce Type: new Abstract: While work on LLM-based regression has largely focused on scalar prediction, multi-output text regression remains less explored. We present DualView, a