4 papers · 1 filter
When Chain-of-Thought Fails, the Solution Hides in the Hidden States
Houman Mehrafarin, Amit Parekh, Ioannis Konstas
Whether intermediate reasoning is computationally useful or merely explanatory depends on whether chain-of-thought (CoT) tokens contain task-relevant information. We present a mech…
FOSSIL: Harnessing Feedback on Suboptimal Samples for Data-Efficient Generalisation with Imitation Learning for Embodied Vision-and-Language Tasks
Sabrina McCallum, Amit Parekh, Alessandro Suglia
Current approaches to embodied AI tend to learn policies from expert demonstrations. However, without a mechanism to evaluate the quality of demonstrated actions, they are limited…
Investigating the Role of Instruction Variety and Task Difficulty in Robotic Manipulation Tasks
Amit Parekh, Nikolas Vitsakis, Alessandro Suglia +1
Evaluating the generalisation capabilities of multimodal models based solely on their performance on out-of-distribution data fails to capture their true robustness. This work intr…
Voices in a Crowd: Searching for Clusters of Unique Perspectives
Nikolas Vitsakis, Amit Parekh, Ioannis Konstas
Language models have been shown to reproduce underlying biases existing in their training data, which is the majority perspective by default. Proposed solutions aim to capture mino…