activity
20242026
most citedSherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Setting

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

Geometry of Values: Task Vector Composition for Ethical Preference Alignment in Language Models

Utkarsh Agarwal, Monojit Choudhury

Large Language Models (LLMs) are increasingly deployed in applications that must weigh clashing moral values, yet even strong models exhibit hidden biases and brittle instruction-f…

cs.LG2026

Multi-Objective Bayesian Optimization for Model Merging

Utkarsh Agarwal, Vamshi Bonagiri, Raul Astudillo +1

Model merging combines trained models directly in weight space, offering a compute-efficient alternative to additional fine-tuning. Selecting merge parameters is nevertheless diffi…

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

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.LG2025

Datasheets Aren't Enough: DataRubrics for Automated Quality Metrics and Accountability

Genta Indra Winata, David Anugraha, Emmy Liu +17

High-quality datasets are fundamental to training and evaluating machine learning models, yet their creation-especially with accurate human annotations-remains a significant challe…

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.CL2025★ 1 cited

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.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…