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researcher

Xing Li

17 papers hereh-index 5149 citations14 works total

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

author position
  • first author2
  • middle author13

Across the 15 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • cs.LG4
  • cs.AI1
  • cs.CV1
  • cs.CY1
  • cs.SE1
same name
  • Xing Li — 18 papers, h 24
  • Xing Li — 10 papers, h 9
  • Xing Li — 6 papers, h 4
  • Xing Li — 6 papers, h 3
  • Xing Li — 5 papers, h 2
  • Xing Li — 4 papers, h 9

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
most citedWhat to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond

1 citations · 2 across the 16 of their papers we have counts for

collaborators
Showing 2025 · cs.CLShow all

4 papers · 2 filters

cs.CL2025

Towards Efficient Agents: A Co-Design of Inference Architecture and System

Weizhe Lin, Hui-Ling Zhen, Shuai Yang +14

The rapid development of large language model (LLM)-based agents has unlocked new possibilities for autonomous multi-turn reasoning and tool-augmented decision-making. However, the…

cs.CL2025

Behavioral Fingerprinting of Large Language Models

Zehua Pei, Hui-Ling Zhen, Ying Zhang +5

Current benchmarks for Large Language Models (LLMs) primarily focus on performance metrics, often failing to capture the nuanced behavioral characteristics that differentiate them.…

cs.CL2025

Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling

Shengyin Sun, Yiming Li, Xing Li +8

Test-time scaling has emerged as a powerful paradigm for enhancing the reasoning capabilities of large language models (LLMs) by allocating additional computational resources durin…

cs.CL2025

Unlocking Efficient Long-to-Short LLM Reasoning with Model Merging

Han Wu, Yuxuan Yao, Shuqi Liu +7

The transition from System 1 to System 2 reasoning in large language models (LLMs) has marked significant advancements in handling complex tasks through deliberate, iterative think…

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