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Xuri Ge

AAAI 2026ACL 2026ICML 2026SIGIR 2026检索与知识强化学习与后训练评测与基准推理可解释性
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0 一作 · 4 篇 · AAAI 2026 / ACL 2026 / ICML 2026 / SIGIR 2026

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2026 顶会论文

4
作者位次 #6/12ACL 2026Poster· Natural Language Processing

Reinforced Efficient Reasoning via Semantically Diverse Exploration

Ziqi Zhao · Zhaochun Ren · Jiahong Zou · Liu Yang · Zhiwei XU · Xuri Ge · Zhumin Chen · xinyu ma · Daiting Shi · Shuaiqiang Wang · Dawei Yin · Xin Xin

摘要

Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte Carlo Tree Search (MCTS)-based extensions improve upon vanilla RLVR (e.g., GRPO) by providing tree-based reasoning rollouts that enable fine-grained and seg...

强化学习与后训练推理可解释性OpenReview 项目页
作者位次 #2/7SIGIR 2026Oral· Information Retrieval (Full)

Differentiable Semantic ID for Generative Recommendation

Junchen Fu · Xuri Ge · Alexandros Karatzoglou · Ioannis Arapakis · Suzan Verberne · Joemon M. Jose · Zhaochun Ren

摘要

Generative recommendation provides a novel paradigm in which each item is represented by a discrete semantic ID (SID) learned from rich content. Most methods treat SIDs as predefined and train recommenders under static indexing. In practice, SIDs are optimized only for content reconstruction rath...

数据与预训练对齐与偏好检索与知识OpenReview

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