activity
20232026
most citedWhen AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation

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

collaborators

14 papers

cs.CL2026

Last Translation Benchmark

Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263

For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…

cs.AI2026

Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results

Jan Batzner, Sree Harsha Nelaturu, Damian Stachura +45

AI evaluations are widely used for testing and understanding progress. However, the diverse evaluators bring with them inconsistencies that challenge analysis and comparison. First…

cs.AI2026

Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting

Avijit Ghosh, Anka Reuel, Jenny Chim +45

AI evaluation results are produced at scale but reported inconsistently across leaderboards, model cards, benchmark papers, and company blogs. The cost is interpretive: readers can…

cs.CL2026

From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs

Itay Itzhak, Eliya Habba, Gabriel Stanovsky +1

Evaluating LLMs is challenging, as benchmark scores often fail to capture models' real-world usefulness. Instead, users often rely on ``vibe-testing'': informal experience-based ev…

cs.CL2026

ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery

Shahar Levy, Eliya Habba, Reshef Mintz +3

Many disciplines pose natural-language research questions over large document collections whose answers typically require structured evidence, traditionally obtained by manually de…

cs.AI2026★ 2 cited

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation

Mubashara Akhtar, Anka Reuel, Prajna Soni +34

Artificial intelligence benchmarks are an important mechanism to measure model progress and guide deployment decisions. However, benchmarks quickly "saturate", making it difficult…

cs.CY2025★ 1 cited

Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations

Anka Reuel, Avijit Ghosh, Jenny Chim +32

Foundation models are increasingly central to high-stakes AI systems, and governance frameworks now depend on evaluations to assess their risks and capabilities. Although general c…

cs.CL2025

JSON Whisperer: Efficient JSON Editing with LLMs

Sarel Duanis, Asnat Greenstein-Messica, Eliya Habba

Large language models (LLMs) can modify JSON documents through natural language commands, but current approaches regenerate entire structures for each edit, resulting in computatio…

cs.CL2025

PromptSuite: A Task-Agnostic Framework for Multi-Prompt Generation

Eliya Habba, Noam Dahan, Gili Lior +1

Evaluating LLMs with a single prompt has proven unreliable, with small changes leading to significant performance differences. However, generating the prompt variations needed for…

cs.CL2025★ 1 cited

ReliableEval: A Recipe for Stochastic LLM Evaluation via Method of Moments

Gili Lior, Eliya Habba, Shahar Levy +2

LLMs are highly sensitive to prompt phrasing, yet standard benchmarks typically report performance using a single prompt, raising concerns about the reliability of such evaluations…

cs.CL2025

DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation

Eliya Habba, Ofir Arviv, Itay Itzhak +5

Recent work found that LLMs are sensitive to a wide range of arbitrary prompt dimensions, including the type of delimiters, answer enumerators, instruction wording, and more. This…

cs.LG2025★ 1 cited

Beyond Benchmarks: On The False Promise of AI Regulation

Gabriel Stanovsky, Renana Keydar, Gadi Perl +1

The performance of AI models on safety benchmarks does not indicate their real-world performance after deployment. This opaqueness of AI models impedes existing regulatory framewor…

cs.CV2024★ 1 cited

Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models

Nitzan Bitton-Guetta, Aviv Slobodkin, Aviya Maimon +6

Imagine observing someone scratching their arm; to understand why, additional context would be necessary. However, spotting a mosquito nearby would immediately offer a likely expla…

cs.CL2023★ 1 cited

The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence

Eliya Habba, Renana Keydar, Dan Bareket +1

We develop computational models to analyze court statements in order to assess judicial attitudes toward victims of sexual violence in the Israeli court system. The study examines…