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20242026
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cs.CL2026

SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs

Debopriyo Banerjee, Kapil Rajesh Kavitha, Angana Borah +11

Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguistic diversity and culturally…

cs.CL2026

Litmus (Re)Agent: A Benchmark and Agentic System for Predictive Evaluation of Multilingual Models

Avni Mittal, Shanu Kumar, Sandipan Dandapat +1

We study predictive multilingual evaluation: estimating how well a model will perform on a task in a target language when direct benchmark results are missing. This problem is comm…

cs.CL2025

Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Setting

Fajri Koto, Rituraj Joshi, Nurdaulet Mukhituly +31

Llama-3.1-Sherkala-8B-Chat, or Sherkala-Chat (8B) for short, is a state-of-the-art instruction-tuned open generative large language model (LLM) designed for Kazakh. Sherkala-Chat (…

cs.CL2025

UNVEILING: What Makes Linguistics Olympiad Puzzles Tricky for LLMs?

Mukund Choudhary, KV Aditya Srivatsa, Gaurja Aeron +6

Large language models (LLMs) have demonstrated potential in reasoning tasks, but their performance on linguistics puzzles remains consistently poor. These puzzles, often derived fr…

cs.CL2025

Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi

Monojit Choudhury, Shivam Chauhan, Rocktim Jyoti Das +27

Developing high-quality large language models (LLMs) for moderately resourced languages presents unique challenges in data availability, model adaptation, and evaluation. We introd…

cs.CL2024

Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability

Haonan Li, Xudong Han, Zenan Zhai +32

To address this gap, we introduce Libra-Leaderboard, a comprehensive framework designed to rank LLMs through a balanced evaluation of performance and safety. Combining a dynamic le…