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20212026
most citedReinforcement Learning with Large Action Spaces for Neural Machine Translation

6 citations · 20 across the 27 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CL2025

Guided Query Refinement: Multimodal Hybrid Retrieval with Test-Time Optimization

Omri Uzan, Asaf Yehudai, Roi pony +2

Multimodal encoders have pushed the boundaries of visual document retrieval, matching textual query tokens directly to image patches and achieving state-of-the-art performance on p…

cs.CL2025

CLEAR: Error Analysis via LLM-as-a-Judge Made Easy

Asaf Yehudai, Lilach Eden, Yotam Perlitz +2

The evaluation of Large Language Models (LLMs) increasingly relies on other LLMs acting as judges. However, current evaluation paradigms typically yield a single score or ranking,…

cs.AI2025

Survey on Evaluation of LLM-based Agents

Asaf Yehudai, Lilach Eden, Alan Li +5

LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environments. This paper provides the f…

cs.CL2025

WildIFEval: Instruction Following in the Wild

Gili Lior, Asaf Yehudai, Ariel Gera +1

Recent LLMs have shown remarkable success in following user instructions, yet handling instructions with multiple constraints remains a significant challenge. In this work, we intr…

cs.CL2025★ 3 cited

Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models

Sonam Gupta, Yatin Nandwani, Asaf Yehudai +3

Fine-tuning Large Language Models (LLMs) on specific datasets is a common practice to improve performance on target tasks. However, this performance gain often leads to overfitting…

cs.CL2025★ 1 cited

The Mighty ToRR: A Benchmark for Table Reasoning and Robustness

Shir Ashury-Tahan, Yifan Mai, Rajmohan C +8

Despite its real-world significance, model performance on tabular data remains underexplored, leaving uncertainty about which model to rely on and which prompt configuration to ado…