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researcher

Rui Sun

University of California, Los Angeles

14 papers hereh-index 6146 citations15 works total

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

author position
  • first author1
  • middle author13

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.CL4
  • cs.AI3
affiliations
  • University of California, Los Angeles
Homepage
same name
  • Rui Sun — 14 papers, h 10
  • Rui Sun — 13 papers, h 11
  • Rui Sun — 10 papers, h 2
  • Rui Sun — 10 papers, h 12
  • Rui Sun — 6 papers, h 5
  • Rui Sun — 6 papers, h 2

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

activity
20222026
most citedIdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models

4 citations · 7 across the 13 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents

Eric Hanchen Jiang, Zhi Zhang, Yuchen Wu +11

Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from graph-structured memo…

cs.CL2026

Why Instruction-Based Unlearning Fails in Diffusion Models?

Zeliang Zhang, Rui Sun, Jiani Liu +2

Instruction-based unlearning has proven effective for modifying the behavior of large language models at inference time, but whether this paradigm extends to other generative model…

cs.CL2026

Agent Q-Mix: Selecting the Right Action for LLM Multi-Agent Systems through Reinforcement Learning

Eric Hanchen Jiang, Levina Li, Rui Sun +9

Large Language Models (LLMs) have shown remarkable performance in completing various tasks. However, solving complex problems often requires the coordination of multiple agents, ra…

cs.CL2026

Aligning Agentic World Models via Knowledgeable Experience Learning

Baochang Ren, Yunzhi Yao, Rui Sun +3

Current Large Language Models (LLMs) exhibit a critical modal disconnect: they possess vast semantic knowledge but lack the procedural grounding to respect the immutable laws of th…

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