6 papers
Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages
Tarek Naous, Anagha Savit, Carlos Rafael Catalan +17
As Large Language Models (LLMs) develop stronger multilingual capabilities, their sensitivity to culturally diverse entities becomes increasingly important. Prior work by Naous et…
Reasoning Model Is Superior LLM-Judge, Yet Suffers from Biases
Hui Huang, Xuanxin Wu, Muyun Yang +1
This paper presents the first systematic comparison investigating whether Large Reasoning Models (LRMs) are superior judges to non-reasoning LLMs. Our empirical analysis yields fou…
DiVA: Fine-grained Factuality Verification with Agentic-Discriminative Verifier
Hui Huang, Muyun Yang, Yuki Arase
Despite the significant advancements of Large Language Models (LLMs), their factuality remains a critical challenge, fueling growing interest in factuality verification. Existing r…
Policy-based Sentence Simplification: Replacing Parallel Corpora with LLM-as-a-Judge
Xuanxin Wu, Yuki Arase, Masaaki Nagata
Sentence simplification aims to modify a sentence to make it easier to read and understand while preserving the meaning. Different applications require distinct simplification poli…
An In-depth Evaluation of Large Language Models in Sentence Simplification with Error-based Human Assessment
Xuanxin Wu, Yuki Arase
Recent studies have used both automatic metrics and human evaluations to assess the simplification abilities of LLMs. However, the suitability of existing evaluation methodologies…
Aligning Sentence Simplification with ESL Learner's Proficiency for Language Acquisition
Guanlin Li, Yuki Arase, Noel Crespi
Text simplification is crucial for improving accessibility and comprehension for English as a Second Language (ESL) learners. This study goes a step further and aims to facilitate…