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researcher

Rui Lu

9 papers hereh-index 81.1k citations10 works total

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

author position
  • first author1
  • middle author7

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG3
  • cs.AI1
  • cs.RO1
same name
  • Rui Lu — 11 papers, h 8
  • Rui Lu — 7 papers, h 4
  • Rui Lu — 6 papers, h 4
  • Rui Lu — 5 papers, h 2
  • Rui Lu — 3 papers, h 3
  • Rui Lu — 3 papers, h 0

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
20232026
most citedGLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

4 citations · 8 across the 9 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

AWM: Answerable Working Memory for Long-Document VQA Agents

Dongzhuoran Zhou, Yuqicheng Zhu, Yule Liu +5

Long-document visual question answering increasingly relies on VLM agents that retrieve candidate pages, inspect page images, write findings to working memory, and synthesize answe…

cs.CL2025

DeepDive: Advancing Deep Search Agents with Knowledge Graphs and Multi-Turn RL

Rui Lu, Zhenyu Hou, Zihan Wang +6

Augmenting large language models (LLMs) with browsing tools substantially improves their potential as deep search agents to solve complex, real-world tasks. Yet, open LLMs still pe…

cs.CL2025★ 4 cited

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

5 Team, Aohan Zeng, Xin Lv +167

We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…

cs.CL2023★ 3 cited

AgentTuning: Enabling Generalized Agent Abilities for LLMs

Aohan Zeng, Mingdao Liu, Rui Lu +4

Open large language models (LLMs) with great performance in various tasks have significantly advanced the development of LLMs. However, they are far inferior to commercial models s…

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