17 citations · 33 across the 41 of their papers we have counts for
11 papers · 1 filter
Differences That Matter: Auditing Models for Capability Gap Discovery and Rectification
Qihao Liu, Chengzhi Mao, Yaojie Liu +2
Conventional evaluation methods for multimodal LLMs (MLLMs) lack interpretability and are often insufficient to fully disclose significant capability gaps across models. To address…
The Universal Weight Subspace Hypothesis
Prakhar Kaushik, Shravan Chaudhari, Ankit Vaidya +2
We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence…
Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
Qihao Liu, Luoxin Ye, Wufei Ma +2
Large language models (LLMs) with explicit reasoning capabilities excel at mathematical reasoning yet still commit process errors, such as incorrect calculations, brittle logic, an…
Perceptual Taxonomy: Evaluating and Guiding Hierarchical Scene Reasoning in Vision-Language Models
Jonathan Lee, Xingrui Wang, Jiawei Peng +9
We propose Perceptual Taxonomy, a structured process of scene understanding that first recognizes objects and their spatial configurations, then infers task-relevant properties suc…
TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing
Eddie Pokming Sheung, Qihao Liu, Wufei Ma +3
With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in…
TGT: Text-Grounded Trajectories for Locally Controlled Video Generation
Guofeng Zhang, Angtian Wang, Jacob Zhiyuan Fang +8
Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior…
PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation
Yifan Yin, Zhengtao Han, Shivam Aarya +6
Fine-grained robot manipulation, such as lifting and rotating a bottle to display the label on the cap, requires robust reasoning about object parts and their relationships with in…
SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models
Wufei Ma, Luoxin Ye, Celso M de Melo +2
Humans naturally understand 3D spatial relationships, enabling complex reasoning like predicting collisions of vehicles from different directions. Current large multimodal models (…
SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning
Wufei Ma, Yu-Cheng Chou, Qihao Liu +4
Despite recent advances on multi-modal models, 3D spatial reasoning remains a challenging task for state-of-the-art open-source and proprietary models. Recent studies explore data-…
DINeMo: Learning Neural Mesh Models with no 3D Annotations
Weijie Guo, Guofeng Zhang, Wufei Ma +1
Category-level 3D/6D pose estimation is a crucial step towards comprehensive 3D scene understanding, which would enable a broad range of applications in robotics and embodied AI. R…
EigenLoRAx: Recycling Adapters to Find Principal Subspaces for Resource-Efficient Adaptation and Inference
Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +1
The rapid growth of large models has raised concerns about their environmental impact and equity in accessibility due to significant computational costs. Low-Rank Adapters (LoRA) o…