1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
RAPID: An Efficient Reinforcement Learning Algorithm for Small Language Models
Lianghuan Huang, Sagnik Anupam, Insup Lee +2
Reinforcement learning (RL) has emerged as a promising strategy for finetuning small language models (SLMs) to solve targeted tasks such as math and coding. However, RL algorithms…
LLM Program Optimization via Retrieval Augmented Search
Sagnik Anupam, Alexander Shypula, Osbert Bastani
Recent work has demonstrated the potential of large language models (LLMs) for program optimization, a key challenge in programming languages. We propose a blackbox adaptation meth…
MathDSL: A Domain-Specific Language for Concise Mathematical Solutions Via Program Synthesis
Sagnik Anupam, Maddy Bowers, Omar Costilla-Reyes +1
We present MathDSL, a Domain-Specific Language (DSL) for mathematical equation solving, which, when deployed in program synthesis models, outperforms state-of-the-art reinforcement…
CapText: Large Language Model-based Caption Generation From Image Context and Description
Shinjini Ghosh, Sagnik Anupam
While deep-learning models have been shown to perform well on image-to-text datasets, it is difficult to use them in practice for captioning images. This is because captions tradit…