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Hongru Cai

ACL 2026SIGIR 2026对齐与偏好多模态推理效率与系统数据与预训练
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1 一作 · 2 篇 · ACL 2026 / SIGIR 2026

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2026 顶会论文

2
作者位次 #4/8ACL 2026Findings· Findings of ACL

O mni- R 1: Towards the Unified Generative Paradigm for Multimodal Reasoning

Dongjie Cheng · Yongqi Li · Zhixin Ma · Hongru Cai · an Jiaotong University) · Wenjie Wang · an Jiaotong University) · Wenjie Li

摘要

Multimodal Large Language Models (MLLMs) are making significant progress in multimodal reasoning. Early approaches focus on pure text-based reasoning. More recent studies have incorporated multimodal information into the reasoning steps; however, they often follow a single task-specific reasoning...

多模态推理对齐与偏好OpenReview 项目页
一作SIGIR 2026Oral· Information Retrieval (Full)

One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment

Hongru Cai · Yongqi Li · Tiezheng Yu · Fengbin ZHU · Wenjie Wang · Fuli Feng · Wenjie Li

摘要

Alignment of Large Language Models (LLMs) aims to align outputs with human preferences, and personalized alignment further adapts models to individual users. This relies on personalized reward models that capture user-specific preferences and automatically provide individualized feedback. However...

对齐与偏好效率与系统数据与预训练OpenReview

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