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Asaf Yehudai

Asaf Yehudai has 5 papers in our library, in 2021–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Akkadian and cuneiform NLP; often with Ariel Gera, Leshem Choshen, Lilach Eden.

5 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 5 · 63 works · 74 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 37 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #7386

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach (2021 · 30 citations)
    Editors of damaged cuneiform tablets fill broken parts from context, and the authors treat this as masked language modelling over Oracc transliterations (about 1M words, 2.3M signs).
  2. A Survey on Evaluation of LLM-based Agents (2026 · 21 citations)
    LLM-based agents pair a backbone model with a harness that adds tools, memory and multi-step control. Because of this, scoring only their text output no longer captures what they can do. The authors present what they call the first comprehensive survey of how such agents are evaluated. They organize the field from…
  3. JuStRank: Benchmarking LLM Judges for System Ranking (2025 · 15 citations)
    LLM judges are usually validated on individual responses or response pairs, without regard to which system produced them.
  4. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs (2026 · 1 citation)
    Large language models are often given tables, yet it is unclear how well they reason over them and how much their answers depend on how a table is written out.
  5. Will it Merge? On The Causes of Model Mergeability (2026)
    Merging combines several fine-tuned models into one multitask model without retraining, yet it is unclear why some fine-tuned updates survive merging better than others.

All works

11 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling ApproachKoren Lazar, Benny Saret, Asaf Yehudai, et al.Semitic languages · 30 citations
  2. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness ↗arXiv (Cornell University) · no summary yetShir Ashury-Tahan et al.2025 · 10 citations
  3. Evaluating and Improving the Coreference Capabilities of Machine Translation Models ↗Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics · no summary yetAsaf Yehudai et al.2023 · 2 citations
  4. Position: Agentic Systems Should be General ↗SSRN Electronic Journal · no summary yetElron Bandel et al.2026
  5. Mediocrity is the key for LLM as a Judge Anchor Selection ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShachar Don-Yehiya et al.2026
  6. Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) · no summary yetAsaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
  7. Teaching Values to Machines: Simulating Human-Like Behavior in LLMs ↗Proceedings of the Fifth Workshop on Generation, Evaluation and Metrics (GEM) · no summary yetAsaf Yehudai, Naama Rozen, Ariel Gera2026

 Co-authors here

12 of 16 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 37 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

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