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Kyle Montgomery

Kyle Montgomery has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Vision & language; often with Chenguang Wang, Dawn Song, Ion Gabriel Stoica.

2 papers in our library · 2024–2026

OpenAlex · h-index 0 · 6 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 98 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #7914

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of California, Santa CruzSanta Cruz · United States2025–2026 · 3 paperscurrent🎓Washington University in St. LouisSt Louis · United States2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArts and Humanities · 1 workArtificial Intelligence · 1 workInformation Systems · 1 workLanguage and Linguistics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 4Research subjects and languages the work is about.Evaluation & benchmarks · 1 workEfficient models & compression · 1 workLanguage models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. JudgeBench: A Benchmark for Evaluating LLM-based Judges (2024 · 101 citations)
    LLM-based judges are now widely used to rank models, act as reward models, and pick the best candidate answers, yet their own reliability is seldom tested.
  2. Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale (2026)
    Visual text compression renders long text as images so a vision-language model can read it with fewer context tokens than the raw text would need.

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. JudgeBench: A Benchmark for Evaluating LLM-based JudgesarXiv:2410.12784Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.2024 · 101 citations
  2. Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at ScaleFindings of the Association for Computational LinguisticsJianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.2026
  3. VMDT: Decoding the Trustworthiness of Video Foundation Models ↗neural information processing systems · no summary yetYujin Potter et al.2025
  4. Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetEric Pasewark et al.2024

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 98 times (of the 149,439 papers whose bibliographies we read); 34 citing papers with a page here →.

Updated

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