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Ying Wen

17 papers hereh-index 11443 citations19 works total

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

author position
  • first author1
  • middle author10
  • last author5

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.AI8
  • cs.CL4
  • cs.LG4
  • cs.CV1
same name
  • Ying Wen — 22 papers, h 25
  • Ying Wen — 16 papers, h 8
  • Ying Wen — 15 papers, h 6
  • Ying Wen — 8 papers, h 5
  • Ying Wen — 7 papers, h 3
  • Ying Wen — 3 papers, h 1

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 citedDS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning

7 citations · 14 across the 15 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

G2-Reader: Dual Evolving Graphs for Multimodal Document QA

Yaxin Du, Junru Song, Yifan Zhou +8

Retrieval-augmented generation is a practical paradigm for question answering over long documents, but it remains brittle for multimodal reading where text, tables, and figures are…

cs.CL2025

ThinkBench: Dynamic Out-of-Distribution Evaluation for Robust LLM Reasoning

Shulin Huang, Linyi Yang, Yan Song +9

Evaluating large language models (LLMs) poses significant challenges, particularly due to issues of data contamination and the leakage of correct answers. To address these challeng…

cs.CL2024

KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning

Peng Yu, Cheng Deng, Beiya Dai +2

Autoregressive large language models (LLMs) pre-trained by next token prediction are inherently proficient in generative tasks. However, their performance on knowledge-driven tasks…

cs.CL2024★ 1 cited

Natural Language Reinforcement Learning

Xidong Feng, Ziyu Wan, Mengyue Yang +5

Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks. However, RL is often hindered by issues such as low sample efficiency, la…

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