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Hengran Zhang

SIGIR 2026×2ACL 2026KDD 2026检索与知识评测与基准对齐与偏好可解释性多模态
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一作贡献70
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合作网络12
2 一作 · 4 篇 · SIGIR 2026 / ACL 2026 / KDD 2026

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2026 顶会论文

4
一作ACL 2026Findings· Findings of ACL

An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLM s

Hengran Zhang · Keping Bi · Jiafeng Guo · Xueqi Cheng

摘要

Relevance and utility are two frequently used measures to evaluate the effectiveness of an information retrieval (IR) system. Relevance emphasizes the aboutness of a result to a query, while utility refers to the result’s usefulness or value to an information seeker. In Retrieval-Augmented Genera...

检索与知识评测与基准对齐与偏好OpenReview 项目页
作者位次 #3/9SIGIR 2026Oral· Information Retrieval (Full)

Reconstructing Content with Collaborative Attention for Universal Multimodal Representation Learning

Jiahan Chen · Da Li · Hengran Zhang · Yinqiong Cai · Lixin Su · Jiafeng Guo · Daiting Shi · Dawei Yin · Keping Bi

摘要

Multimodal embedding models, rooted in multimodal large language models (MLLMs), have yielded significant performance improvements across diverse tasks such as retrieval and classification. However, most existing approaches rely heavily on large-scale contrastive learning and offer limited explor...

可解释性多模态效率与系统OpenReview

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