1 citations · 1 across the 3 of their papers we have counts for
3 papers · 1 filter
LLMs Get Smarter from Targeted Synthetic Multilingual Data
Ishika Agarwal, Arkajyoti Charaborty, Tanner Sorensen +2
Language-specific competency (LSC) is the phenomenon of a language model performing better or worse depending on the language of the prompt. In other words, a language model output…
When Actions Teach You to Think: Reasoning-Action Synergy via Reinforcement Learning in Conversational Agents
Mrinal Rawat, Arkajyoti Chakraborty, Neha Gupta +1
Supervised fine-tuning (SFT) has emerged as one of the most effective ways to improve the performance of large language models (LLMs) in downstream tasks. However, SFT can have dif…
DySK-Attn: A Framework for Efficient, Real-Time Knowledge Updating in Large Language Models via Dynamic Sparse Knowledge Attention
Kabir Khan, Priya Sharma, Arjun Mehta +2
Large Language Models (LLMs) suffer from a critical limitation: their knowledge is static and quickly becomes outdated. Retraining these massive models is computationally prohibiti…