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Xiaoguang Li

10 papers hereh-index 578 citations15 works total

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

author position
  • middle author8
  • last author1

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL6
  • cs.AI3
  • cs.LG1
same name
  • Xiaoguang Li — 11 papers, h 11
  • Xiaoguang Li — 9 papers, h 3
  • Xiaoguang Li — 8 papers, h 6
  • Xiaoguang Li — 7 papers, h 16
  • Xiaoguang Li — 6 papers, h 10
  • Xiaoguang Li — 6 papers, h 10

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
20242026
collaborators
Showing 2026Show all

4 papers · 1 filter

cs.LG2026

Beyond Outcome Rewards: Step-Level Self-Distilled Policy Optimization for Deep Search Agents

Haoze Wu, Chuqiao Kuang, Tianyi Zhuang +1

Deep search agents operate over trajectories spanning dozens of steps, yet standard reinforcement learning provides only a single outcome reward per trajectory, which is far too sp…

cs.AI2026

KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering

Yike Wu, Nan Hu, Guilin Qi +11

Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream knowledge-intensive tasks, parti…

cs.AI2026

UIS-Digger: Towards Comprehensive Research Agent Systems for Real-world Unindexed Information Seeking

Chang Liu, Chuqiao Kuang, Tianyi Zhuang +4

Recent advancements in LLM-based information-seeking agents have achieved record-breaking performance on established benchmarks. However, these agents remain heavily reliant on sea…

cs.CL2026

Gradually Excavating External Knowledge for Implicit Complex Question Answering

Chang Liu, Xiaoguang Li, Lifeng Shang +4

Recently, large language models (LLMs) have gained much attention for the emergence of human-comparable capabilities and huge potential. However, for open-domain implicit question-…

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