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Peng Shi

6 papers hereh-index 5251 citations8 works total

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

author position
  • middle author5

Across the 5 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.AI1
  • cs.CR1
same name
  • Peng Shi — 19 papers, h 61
  • Peng Shi — 19 papers, h 4
  • Peng Shi — 10 papers, h 7
  • Peng Shi — 10 papers, h 2
  • Peng Shi — 9 papers, h 18
  • Peng Shi — 9 papers, h 8

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
20232025
most citedOpenAgents: An Open Platform for Language Agents in the Wild

11 citations · 20 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024

You Only Read Once (YORO): Learning to Internalize Database Knowledge for Text-to-SQL

Hideo Kobayashi, Wuwei Lan, Peng Shi +5

While significant progress has been made on the text-to-SQL task, recent solutions repeatedly encode the same database schema for every question, resulting in unnecessary high infe…

cs.CL2024★ 9 cited

RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation

Dongyu Ru, Lin Qiu, Xiangkun Hu +15

Despite Retrieval-Augmented Generation (RAG) showing promising capability in leveraging external knowledge, a comprehensive evaluation of RAG systems is still challenging due to th…

cs.CL2023★ 11 cited

OpenAgents: An Open Platform for Language Agents in the Wild

Tianbao Xie, Fan Zhou, Zhoujun Cheng +13

Language agents show potential in being capable of utilizing natural language for varied and intricate tasks in diverse environments, particularly when built upon large language mo…

cs.CL2023

Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation

Ali Mousavi, Xin Zhan, He Bai +9

Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be used to train forward and reverse neural models that generate text from KG and vice versa. However models t…

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