arXiv AI

Auditing Agent Actions through Query-Conditioned Attribution

arXiv AI

Aug 10

Long-Horizon Agent Trajectory Attribution: A Unified Benchmark and Fine-Grained Annotation Framework

arXiv:2608. 06909v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate through long-horizon trajectories involving user instructions, tool use, external observations, and memory.

By Jing Chen, Yang Sun, Li Zhang, Lin Xu, Jie Shi

llms agents benchmarks safety

arXiv AI

Sep 15

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

The paper introduces Continual Search, an iterative framework that guides large language models to persistently search for diagnostic evidence in long AI agent execution logs, addressing the limitations of one-shot judgments. Evaluated on four existing RCA benchmarks and a new large-scale dataset called MegaRCA-Mix, Continual Search consistently boosts attribution performance, achieving a 40% F1 improvement for GPT‑5.5 on MegaRCA‑Mix. The results show that effective search can outweigh raw model scale, enabling lower-tier models to outperform higher-tier ones in root‑cause attribution tasks.

By Harsh Raj, David Lee, Anas Mahmoud, Renxiong Wang, Razvan-Gabriel Dumitru, Chenguang Wang, Tong Zhao, Yunzhong He, Darvin Yi, Vipul Gupta

llms agents benchmarks

arXiv AI

Aug 7

SearchAuditor: Auditing and Attributing Failures in Long-Horizon Search Agents

arXiv:2608. 05212v1 Announce Type: new Abstract: Deep search agents tackle challenging questions through long-horizon web interactions, a process that is both complex and fragile: small reasoning errors may propagate through long, noisy trajectories into fluent but incorrect answers.

By Zhixiang Liang, Yifei Liu, Yidan Huang, Haozhe Zhao, Beichen Huang, Jiaqi Wang, Nan Duan, Qiong Cao

llms agents benchmarks

arXiv AI

Jun 3

Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation

arXiv:2606. 03128v1 Announce Type: cross Abstract: Smart contracts face critical security challenges that require thorough auditing in decentralized web services.

By Bagus Rakadyanto Oktavianto Putra, Muhamad Risqi Utama Saputra, Widyawan, Guntur Dharma Putra

llms efficiency benchmarks safety

arXiv AI

Aug 11

READER: Dynamic LLM Provenance from Query-Varying Interactions

arXiv:2606. 10794v3 Announce Type: replace Abstract: Existing black-box LLM provenance methods achieve comparability by querying every candidate model with the same diagnostic prompts.

By Jiaxu Liu, Sunnan Mu, Dong Huang, Liuyin Wang, Jing Shao, Jie Zhang

llms agents

arXiv AI

Sep 10

DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents

arXiv:2609.06059v1 Announce Type: new Abstract: As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to a...

By Yu Liu, Zhilin Liu, Zhiwei Yang, Shaojie Zhang, Zheyuan Deng, Tingwei Huang, Zhenbo Luo, Lei Jiang, Yanbing Liu, Pei Fu

llms agents multimodal benchmarks safety

arXiv Machine Learning

Sep 22

EAVer: Long-Form Factuality Verification as an End-to-End Agentic Policy

arXiv:2609.22223v1 Announce Type: cross Abstract: Long-form factuality verification is commonly implemented as a static decompose-search-verify pipeline, with separately prompted modules processing c...

By Kening Zheng, Aoying Zheng, Zhigang Chang, Yazhi Guo, Miaotian Guo, Qingwei Zong, Xianhai Xie, Weiqiang Jin, Chengze Li, Hanrong Zhang, Jie Yang, Wei-Chieh Huang, Lingzhe Zhang, Liancheng Fang, Xin Zou, Hanqian Li, Jiahao Huo, Yibo Yan, Zizhuang Deng, Lei Miao, Wei Guo, Haihong Tang, Bo Zheng, Philip S. Yu

llms agents reinforcement-learning benchmarks safety

arXiv AI

Aug 10

An End-to-End Agent Auditing Engine

arXiv:2608. 07346v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of domains.

By Haoning Wang, Mingxun Zhang, Chenyue Yu, Yingjun Shang, Xia Hu, Guanchu Wang, Na Zou

llms agents

arXiv AI

Aug 11

$A^2E$ : An End-to-End Agent Auditing Engine

arXiv:2608. 07346v2 Announce Type: replace Abstract: With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of domains.

By Haoning Wang, Mingxun Zhang, Chenyue Yu, Yingjun Shang, Xia Hu, Guanchu Wang, Na Zou

llms agents

arXiv AI

Jun 2

Where Do Deep-Research Agents Go Wrong? Span-Level Error Localization in Agent Trajectories

arXiv:2606. 02060v1 Announce Type: new Abstract: Deep-research agents solve tasks through long trajectories of search, tool use, evidence inspection, and answer synthesis.

By Jiaming Wang, Ziteng Feng, Jiangtao Wu, Ruihao Li, Qianqian Xie, Yuxiang Ren, He Zhu, Xueming Han, Fanyu Meng, Junlan Feng, Jiaheng Liu

llms agents benchmarks

arXiv AI

Aug 11

PluginEval: A Diagnostic Benchmark for Fine-Grained Error Attribution in Function Calling

arXiv:2608. 08700v1 Announce Type: new Abstract: Reliable evaluation of tool routing is critical as Large Language Models increasingly operate as autonomous agents.

By Dongjie Xu, Julius, Hanchi Dong, Minghua Tang, Yuxuan Sun, Ziwei Nie, Zicheng Liu, Dujun Qing, Jiajie Xu

llms agents benchmarks safety

arXiv AI

Jul 28

Beyond Shapley: An Influence-Based Data Auditing Pipeline for LLM Alignment and Evaluation

arXiv:2607. 22766v1 Announce Type: cross Abstract: The alignment of Large Language Models (LLMs) is increasingly bottlenecked by data quality.

By Yunting Song, Matthew Watson, Peter Grabowski, Jun Qin

llms reinforcement-learning benchmarks safety data-engineering

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