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20242026
most citedStructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

2 citations · 4 across the 16 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

AgentPersonaBench: Benchmarking Persona-Driven User Simulation

Jintao Huang, Yifan Wang, Hongyu Shen +43

We introduce AgentPersonaBench (APB), a benchmark evaluating whether persona conditioning faithfully steers downstream agent behavior. While language models are increasingly deploy…

cs.CL2026

Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs

Xiaoyu Guo, Pengcheng Chen, Jiong Yu +3

Graph-augmented large language models often assume that graph evidence produced by external computation and placed in the input can be used by the native decoder. We test this assu…

cs.AI2026

Dr-DCI: Scaling Direct Corpus Interaction via Dynamic Workspace Expansion

Yi Lu, Zhuofeng Li, Ping Nie +7

Agentic search over large corpora relies on retriever-mediated interfaces (e.g., BM25 or ColBERT) for scalable candidate discovery. While effective at ranking relevant documents, t…

cs.CL2026

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

Zhuofeng Li, Yi Lu, Dongfu Jiang +7

The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-based reviewers often generate s…

cs.CL2026

ClawBench: Can AI Agents Complete Everyday Online Tasks?

Yuxuan Zhang, Yubo Wang, Yipeng Zhu +25

AI agents may be able to assist with emails and documents, but can they reliably complete everyday online workflows on real websites? Everyday online tasks offer a realistic yet un…

cs.SE2026

SWE-QA-Pro: A Representative Benchmark and Scalable Training Recipe for Repository-Level Code Understanding

Songcheng Cai, Zhiheng Lyu, Yuansheng Ni +13

Agentic repository-level code understanding is essential for automating complex software engineering tasks, yet the field lacks reliable benchmarks. Existing evaluations often over…