14 citations · 14 across the 10 of their papers we have counts for
10 papers
Learning Action Priors for Cross-embodiment Robot Manipulation
Dong Jing, Tianqi Zhang, Jiaqi Liu +5
Most Vision-Language-Action (VLA) models build on a Vision-Language Model (VLM) backbone by attaching an action module and optimizing the full policy jointly. This design inherits…
DeepRoot: A KG-Coordinated Multi-Agent System for Therapeutic Reasoning over Historical Medical Texts
Zijian Carl Ma, Sean J. Wang, Sijbren Kramer +1
Historical medical archives and traditional medicines hold immense potential for drug discovery and remain a primary source for current drug development. However, pre-ontological p…
TIPS: Turn-Level Information-Potential Reward Shaping for Search-Augmented LLMs
Yutao Xie, Nathaniel Thomas, Nicklas Hansen +3
Search-augmented large language models (LLMs) trained with reinforcement learning (RL) have achieved strong results on open-domain question answering (QA), but training still remai…
Rethinking Intermediate Representation for VLM-based Robot Manipulation
Weiliang Tang, Jialin Gao, Jia-Hui Pan +6
Vision-Language Model (VLM) is an important component to enable robust robot manipulation. Yet, using it to translate human instructions into an action-resolvable intermediate repr…
Incentivizing Multimodal Reasoning in Large Models for Direct Robot Manipulation
Weiliang Tang, Dong Jing, Jia-Hui Pan +5
Recent Large Multimodal Models have demonstrated remarkable reasoning capabilities, especially in solving complex mathematical problems and realizing accurate spatial perception. O…
Digi-Q: Learning Q-Value Functions for Training Device-Control Agents
Hao Bai, Yifei Zhou, Li Erran Li +2
While a number of existing approaches for building foundation model agents rely on prompting or fine-tuning with human demonstrations, it is not sufficient in dynamic environments…
GeoManip: Geometric Constraints as General Interfaces for Robot Manipulation
Weiliang Tang, Jia-Hui Pan, Yun-Hui Liu +4
We present GeoManip, a framework to enable generalist robots to leverage essential conditions derived from object and part relationships, as geometric constraints, for robot manipu…
Language Models Can Reduce Asymmetry in Information Markets
Nasim Rahaman, Martin Weiss, Manuel Wüthrich +4
This work addresses the buyer's inspection paradox for information markets. The paradox is that buyers need to access information to determine its value, while sellers need to limi…
Learning 3D object-centric representation through prediction
John Day, Tushar Arora, Jirui Liu +2
As part of human core knowledge, the representation of objects is the building block of mental representation that supports high-level concepts and symbolic reasoning. While humans…
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation
Yi-Fan Zhang, Hanlin Zhang, Zachary C. Lipton +2
Previous works on Treatment Effect Estimation (TEE) are not in widespread use because they are predominantly theoretical, where strong parametric assumptions are made but untractab…