2 citations · 2 across the 8 of their papers we have counts for
8 papers
GPTNT: Benchmarking Real-Time Collaboration Between Multimodal Agents on Keep Talking And Nobody Explodes
Amit Parekh, Sabrina McCallum, Kareem Al-Hasan +3
Multimodal models are increasingly deployed to solve tasks collaboratively with humans or other artificial agents. While existing benchmarks show that they possess the fundamental…
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…
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…
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…
Learning To See But Forgetting To Follow: Visual Instruction Tuning Makes LLMs More Prone To Jailbreak Attacks
Georgios Pantazopoulos, Amit Parekh, Malvina Nikandrou +1
Augmenting Large Language Models (LLMs) with image-understanding capabilities has resulted in a boom of high-performing Vision-Language models (VLMs). While studying the alignment…
Multitask Multimodal Prompted Training for Interactive Embodied Task Completion
Georgios Pantazopoulos, Malvina Nikandrou, Amit Parekh +6
Interactive and embodied tasks pose at least two fundamental challenges to existing Vision & Language (VL) models, including 1) grounding language in trajectories of actions and ob…
iLab at SemEval-2023 Task 11 Le-Wi-Di: Modelling Disagreement or Modelling Perspectives?
Nikolas Vitsakis, Amit Parekh, Tanvi Dinkar +3
There are two competing approaches for modelling annotator disagreement: distributional soft-labelling approaches (which aim to capture the level of disagreement) or modelling pers…