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Xin Chen

6 papers hereh-index 16 citations7 works total

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

author position
  • middle author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.CV1
  • cs.LG1
same name
  • Xin Chen — 33 papers, h 12
  • Xin Chen — 20 papers, h 5
  • Xin Chen — 15 papers, h 17
  • Xin Chen — 15 papers, h 13
  • Xin Chen — 15 papers, h 15
  • Xin Chen — 13 papers, h 41

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 citedOn the Roles of LLMs in Planning: Embedding LLMs into Planning Graphs

3 citations · 3 across the 6 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Making AI Scientists Auditable from Evidence to Claim

Zijian Wang, Hanqi Li, Ziyue Yang +17

AI research systems can report improved results without establishing that the tested implementation matches the method described in their conclusions. We introduce Xcientist, a res…

cs.AI2026

Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning

Tianyuan Shi, Canbin Huang, Bei Li +4

Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferring what to answer rather th…

cs.AI2026

PseudoAct: Leveraging Pseudocode Synthesis for Flexible Planning and Action Control in Large Language Model Agents

Yihan, Wen, Xin Chen

Large language model (LLM) agents typically rely on reactive decision-making paradigms such as ReAct, selecting actions conditioned on growing execution histories. While effective…

cs.AI2024★ 3 cited

On the Roles of LLMs in Planning: Embedding LLMs into Planning Graphs

Hankz Hankui Zhuo, Xin Chen, Rong Pan

Plan synthesis aims to generate a course of actions or policies to transit given initial states to goal states, provided domain models that could be designed by experts or learnt f…

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