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Heng Wang

University of Illinois Urbana-Champaign

4 papers hereh-index 81.1k citations14 works total

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

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CV1
  • cs.IR1
  • cs.LG1
affiliations
  • University of Illinois Urbana-Champaign
Homepage
same name
  • Heng Wang — 12 papers, h 24
  • Heng Wang — 12 papers, h 8
  • Heng Wang — 10 papers, h 11
  • Heng Wang — 9 papers, h 7
  • Heng Wang — 5 papers
  • Heng Wang — 5 papers, h 39

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 citedKimi-VL Technical Report

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

collaborators

4 papers

cs.LG2025

Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment

Yizhuo Zhang, Heng Wang, Shangbin Feng +3

Previous research has sought to enhance the graph reasoning capabilities of LLMs by supervised fine-tuning on synthetic graph data. While these led to specialized LLMs better at so…

cs.IR2025

Unveiling the Hidden: Movie Genre and User Bias in Spoiler Detection

Haokai Zhang, Shengtao Zhang, Zijian Cai +4

Spoilers in movie reviews are important on platforms like IMDb and Rotten Tomatoes, offering benefits and drawbacks. They can guide some viewers' choices but also affect those who…

cs.CV2025★ 1 cited

Kimi-VL Technical Report

Kimi Team, Angang Du, Bohong Yin +92

We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…

cs.AI2024

Explaining Datasets in Words: Statistical Models with Natural Language Parameters

Ruiqi Zhong, Heng Wang, Dan Klein +1

To make sense of massive data, we often fit simplified models and then interpret the parameters; for example, we cluster the text embeddings and then interpret the mean parameters…

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