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Hao Jiang

4 papers hereh-index 329 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • cs.IR1
same name
  • Hao Jiang — 43 papers, h 81
  • Hao Jiang — 25 papers, h 8
  • Hao Jiang — 23 papers, h 12
  • Hao Jiang — 23 papers, h 4
  • Hao Jiang — 18 papers, h 15
  • Hao Jiang — 11 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedAn Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models

6 citations · 6 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2026

AVOC: Enhancing Hour-Level Audio-Video Understanding in Omni-Modal LLMs via Retrieval-Inspired Token Compression

Yijing Chen, Wenhui Tan, Xiaoyi Yu +7

Multimodal Large Language Models have achieved remarkable progress in short-form audio-video understanding, yet long-form audio-video comprehension remains challenged by limited co…

cs.LG2026

DiPOD: Diffusion Policy Optimization without Drifting Apart

Haozhe Jiang, Haiwen Feng, Pieter Abbeel +3

RL post-training has become increasingly pivotal for improving diffusion policies, but existing diffusion policy-gradient methods are often unstable and cannot achieve reliable pol…

cs.LG2026

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning

Hao Jiang, Enneng Yang, Guojie Zhu +7

Continual learning capability is critical for Industrial LLMs, as deployed models must be continuously updated to meet evolving requirements and environments, rather than repeatedl…

cs.IR2024★ 6 cited

An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models

Qi Liu, Gang Guo, Jiaxin Mao +5

With the development of pre-trained language models, the dense retrieval models have become promising alternatives to the traditional retrieval models that rely on exact match and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.