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Junbo Qi

SIGIR 2026×3ACL 2026强化学习与后训练推理多模态对齐与偏好评测与基准
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2 一作 · 4 篇 · SIGIR 2026 / ACL 2026

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2026 顶会论文

4
一作ACL 2026Poster· Natural Language Processing

E - V i C : Reasoning Beyond Text via Embodied Visual Chain for Spatial Intelligence

Junbo Qi · Yi Zhang · Hanchu Ni · Che Liu · Zhimin Yao · Ruilin Yang · Xiancong Ren · Liangjian Wen · Wei Ge · Yuya Ieiri · Osamu Yoshie · Yong Dai · Xiaozhu Ju

摘要

Precise spatial reasoning is fundamental to embodied intelligence, yet current Vision-Language Models (VLMs) remain bottlenecked by text-based Chain-of-Thought (CoT) that relies solely on textual reasoning trajectories, often bypassing active engagement with fine-grained visual details. To addres...

推理多模态评测与基准OpenReview 项目页
一作SIGIR 2026Oral· Information Retrieval (Full)

Adaptive Mix Preference Optimization for Generative Recommendation

Junbo Qi · Yanyan Zou · Xuanhua Yang · Sulong Xu · Ying Sun · Shengjie Li

摘要

Recommender systems aim to leverage user interaction signals to recommend items that users are likely to be interested in. Motivated by the success of Large Language Model (LLMs), generative recommendation (GR) has recently gained increasing attention, typically following a two-stage paradigm: su...

对齐与偏好检索与知识强化学习与后训练OpenReview
作者位次 #7/8SIGIR 2026Poster· Information Retrieval (Industry)

Breaking the Relevance–Diversity Seesaw: Hierarchical LLM Reasoning with RL for Industrial Novelty Recommendation

Ying Sun · Yanyan Zou · Xiao Wang · Hanchuan Xu · Xuanhua Yang · Sulong Xu · Junbo Qi · Shengjie Li

摘要

Novelty recommendation sustains long-term user engagement by exposing users to content that is both relevant and meaningfully different from their recent consumption. In large-scale e-commerce, this requires composing coherent yet non-redundant recommendation lists, a task fundamentally constrain...

强化学习与后训练推理多模态OpenReview
作者位次 #2/10SIGIR 2026Poster· Information Retrieval (Industry)

GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation

Yanyan Zou · Junbo Qi · Lunsong Huang · Yu Li · Kewei Xu · Jiahao Gao · Binglei Zhao · Xuanhua Yang · Sulong Xu · Shengjie Li

摘要

Generative Retrieval (GR) offers a promising paradigm for recommendation through next-token prediction (NTP). However, scaling it to large-scale industrial systems introduces three challenges: (i) within a single request, the identical model inputs may produce inconsistent outputs due to the pagi...

对齐与偏好强化学习与后训练可解释性OpenReview

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