activity
20242026
collaborators
Showing 2025Show all

11 papers · 1 filter

cs.RO2025

PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly

Liang Ma, Jiajun Wen, Min Lin +12

While vision-language models (VLMs) have demonstrated promising capabilities in reasoning and planning for embodied agents, their ability to comprehend physical phenomena, particul…

cs.LG2025

MALT: Improving Reasoning with Multi-Agent LLM Training

Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das +6

Large Language Models (LLMs) often produce answers with a single chain-of-thought, which restricts their ability to explore reasoning paths or self-correct flawed outputs in comple…

cs.CL2025

A Culturally-diverse Multilingual Multimodal Video Benchmark & Model

Bhuiyan Sanjid Shafique, Ashmal Vayani, Muhammad Maaz +26

Large multimodal models (LMMs) have recently gained attention due to their effectiveness to understand and generate descriptions of visual content. Most existing LMMs are in Englis…

cs.CV2025

DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models

Komal Kumar, Rao Muhammad Anwer, Fahad Shahbaz Khan +3

Efficient fine-tuning of pre-trained Text-to-Image (T2I) models involves adjusting the model to suit a particular task or dataset while minimizing computational resources and limit…

cs.CV2025

How Good are Foundation Models in Step-by-Step Embodied Reasoning?

Dinura Dissanayake, Ahmed Heakl, Omkar Thawakar +9

Embodied agents operating in the physical world must make decisions that are not only effective but also safe, spatially coherent, and grounded in context. While recent advances in…

cs.RO2025

MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation

Harsh Singh, Rocktim Jyoti Das, Mingfei Han +2

Large Language Models (LLMs) have demonstrated remarkable planning abilities across various domains, including robotics manipulation and navigation. While recent efforts in robotic…