6 citations · 15 across the 3 of their papers we have counts for
4 papers
Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
Christian Walder, Deep Karkhanis
Reinforcement Learning (RL) algorithms sample multiple n>1 solution attempts for each problem and reward them independently. This optimizes for pass@1 performance and prioritizes t…
Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive
Arka Pal, Deep Karkhanis, Samuel Dooley +3
Direct Preference Optimisation (DPO) is effective at significantly improving the performance of large language models (LLMs) on downstream tasks such as reasoning, summarisation, a…
Giraffe: Adventures in Expanding Context Lengths in LLMs
Arka Pal, Deep Karkhanis, Manley Roberts +3
Modern large language models (LLMs) that rely on attention mechanisms are typically trained with fixed context lengths which enforce upper limits on the length of input sequences t…
Sentiment Analysis: Predicting Yelp Scores
Bhanu Prakash Reddy Guda, Mashrin Srivastava, Deep Karkhanis
In this work, we predict the sentiment of restaurant reviews based on a subset of the Yelp Open Dataset. We utilize the meta features and text available in the dataset and evaluate…