2 citations · 4 across the 11 of their papers we have counts for
4 papers · 1 filter
Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval
Davide Buoso, Luke Robinson, Giuseppe Averta +3
This study explores the potential of off-the-shelf Vision-Language Models (VLMs) for high-level robot planning in the context of autonomous navigation. Indeed, while most of existi…
HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits
Tim Franzmeyer, Aleksandar Shtedritski, Samuel Albanie +3
Benchmarks have been essential for driving progress in machine learning. A better understanding of LLM capabilities on real world tasks is vital for safe development. Designing ade…
Select to Perfect: Imitating desired behavior from large multi-agent data
Tim Franzmeyer, Edith Elkind, Philip Torr +2
AI agents are commonly trained with large datasets of demonstrations of human behavior. However, not all behaviors are equally safe or desirable. Desired characteristics for an AI…
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection
Linas Nasvytis, Kai Sandbrink, Jakob Foerster +2
While reinforcement learning (RL) algorithms have been successfully applied across numerous sequential decision-making problems, their generalization to unforeseen testing environm…