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Le Yu

ACL 2026×2推理对齐与偏好评测与基准效率与系统多模态
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #9/16ACL 2026Poster· Natural Language Processing

Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models

Binghai Wang · Yantao Liu · Yuxuan Liu · Tianyi Tang · Shenzhi Wang · Chang Gao · Chujie Zheng · Yichang Zhang · Le Yu · Shixuan Liu · Tao Gui · Qi Zhang · Xuanjing Huang · Bowen Yu · Fei Huang · Junyang Lin

摘要

Generative Reward Models (GenRMs) and LLM-as-a-Judge exhibit deceptive alignment by producing correct judgments for incorrect reasons, as they are trained and evaluated to prioritize Outcome Accuracy , which undermines their ability to generalize during RLHF. We introduce Rationale Consistency ,...

对齐与偏好评测与基准推理OpenReview 项目页
作者位次 #2/8ACL 2026Findings· Findings of ACL

On the Editability of Delta Parameters in Post-Trained Models

Qiaoyu Tang · Le Yu · Bowen Yu · Hongyu Lin · Keming Lu · Yaojie Lu · Xianpei Han · Le Sun

摘要

Post-training has emerged as a crucial paradigm for adapting large-scale pre-trained models to various tasks, whose effects are fully reflected by delta parameters (i.e., the disparity between post-trained and pre-trained parameters).While numerous studies have explored delta parameter properties...

效率与系统推理多模态OpenReview 项目页

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