33 citations · 113 across the 33 of their papers we have counts for
8 papers · 1 filter
Emma-X: An Embodied Multimodal Action Model with Grounded Chain of Thought and Look-ahead Spatial Reasoning
Qi Sun, Pengfei Hong, Tej Deep Pala +4
Traditional reinforcement learning-based robotic control methods are often task-specific and fail to generalize across diverse environments or unseen objects and instructions. Visu…
MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures
Jinjie Ni, Yifan Song, Deepanway Ghosal +10
Perceiving and generating diverse modalities are crucial for AI models to effectively learn from and engage with real-world signals, necessitating reliable evaluations for their de…
Not All Votes Count! Programs as Verifiers Improve Self-Consistency of Language Models for Math Reasoning
Vernon Y. H. Toh, Deepanway Ghosal, Soujanya Poria
Large language models (LLMs) have shown increasing competence in solving mathematical reasoning problems. However, many open-source LLMs still struggle with errors in calculation a…
Improving Text-To-Audio Models with Synthetic Captions
Zhifeng Kong, Sang-gil Lee, Deepanway Ghosal +5
It is an open challenge to obtain high quality training data, especially captions, for text-to-audio models. Although prior methods have leveraged \textit{text-only language models…
Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization
Navonil Majumder, Chia-Yu Hung, Deepanway Ghosal +3
Generative multimodal content is increasingly prevalent in much of the content creation arena, as it has the potential to allow artists and media personnel to create pre-production…
Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal Reasoning
Deepanway Ghosal, Vernon Toh Yan Han, Chia Yew Ken +1
This paper introduces the novel task of multimodal puzzle solving, framed within the context of visual question-answering. We present a new dataset, AlgoPuzzleVQA designed to chall…