22 citations · 31 across the 10 of their papers we have counts for
5 papers · 1 filter
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis
Rohan Mitta, Hosein Hasanbeig, Jun Wang +3
This paper addresses the problem of maintaining safety during training in Reinforcement Learning (RL), such that the safety constraint violations are bounded at any point during le…
Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
Jun Wang, Hosein Hasanbeig, Kaiyuan Tan +2
This paper addresses the problem of designing control policies for agents with unknown stochastic dynamics and control objectives specified using Linear Temporal Logic (LTL). Recen…
Decoding In-Context Learning: Neuroscience-inspired Analysis of Representations in Large Language Models
Safoora Yousefi, Leo Betthauser, Hosein Hasanbeig +2
Large language models (LLMs) exhibit remarkable performance improvement through in-context learning (ICL) by leveraging task-specific examples in the input. However, the mechanisms…
ALLURE: Auditing and Improving LLM-based Evaluation of Text using Iterative In-Context-Learning
Hosein Hasanbeig, Hiteshi Sharma, Leo Betthauser +2
From grading papers to summarizing medical documents, large language models (LLMs) are evermore used for evaluation of text generated by humans and AI alike. However, despite their…
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira +5
Recently an influx of studies claim emergent cognitive abilities in large language models (LLMs). Yet, most rely on anecdotes, overlook contamination of training sets, or lack syst…