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Kangning Zhang

ACL 2026×2NeurIPS 2026智能体与工具评测与基准多模态推理对齐与偏好
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2 一作 · 3 篇 · ACL 2026 / NeurIPS 2026

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2026 顶会论文

3
作者位次 #5/11ACL 2026Poster· Natural Language Processing

A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage

Congmin Zheng · Jiachen Zhu · Zhuoying Ou · Yuxiang Chen · Kangning Zhang · Rong Shan · Zeyu Zheng · Mengyue Yang · Ruiming Tang (Huawei Noah&#x27 · s Ark Lab) · Ruiming Tang (Huawei Noah&#x27

摘要

Large Language Models (LLMs) have advanced reasoning ability, yet conventional alignment remains dominated by outcome reward models (ORMs) that judge only final answers. Process Reward Models(PRMs) address this gap by evaluating and guiding reasoning at the step or trajectory level. This survey p...

推理评测与基准对齐与偏好OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

L oop T ool: Closing the Data–Training Loop for Robust LLM Tool Calls

Kangning Zhang · Weiwen Liu · Wenxiang Jiao · Kounianhua Du · Yuan Lu · Ruiming Tang (Huawei Noah&#x27 · s Ark Lab)

摘要

Augmenting Large Language Models (LLMs) with external tools enables them to execute complex, multi-step tasks. However, tool learning is hampered by the static synthetic data pipelines, where data generation and model training are executed as two separate, non-interactive processes. This approach...

智能体与工具评测与基准数据与预训练OpenReview 项目页

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