1 citations · 1 across the 6 of their papers we have counts for
7 papers
EmbodiedMind: Adaptive Data Curation and Prefix-Tree Reinforcement Learning for Efficient Embodied Intelligence
Feifan Wang, Zongbing Zhang, Yu Zhang +8
Training embodied foundation models typically requires massive-scale datasets and extensive computational resources, yet often suffers from three critical limitations: (1) ineffici…
Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)
Harshdeep Singh, Yurui Zhu, Giovanni Colavizza +1
We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale. We address two questions in s…
Benchmarking Large Language Models on Reference Extraction and Parsing in the Social Sciences and Humanities
Yurui Zhu, Giovanni Colavizza, Matteo Romanello
Bibliographic reference extraction and parsing are foundational for citation indexing, linking, and downstream scholarly knowledge-graph construction. However, most established eva…
Co-Sight: Enhancing LLM-Based Agents via Conflict-Aware Meta-Verification and Trustworthy Reasoning with Structured Facts
Hongwei Zhang, Ji Lu, Shiqing Jiang +11
Long-horizon reasoning in LLM-based agents often fails not from generative weakness but from insufficient verification of intermediate reasoning. Co-Sight addresses this challenge…
EmbodiedBrain: Expanding Performance Boundaries of Task Planning for Embodied Intelligence
Ding Zou, Feifan Wang, Mengyu Ge +17
The realization of Artificial General Intelligence (AGI) necessitates Embodied AI agents capable of robust spatial perception, effective task planning, and adaptive execution in ph…
Rethinking the Generation of High-Quality CoT Data from the Perspective of LLM-Adaptive Question Difficulty Grading
Qianjin Yu, Keyu Wu, Zihan Chen +7
Recently, DeepSeek-R1 (671B) (DeepSeek-AIet al., 2025) has demonstrated its excellent reasoning ability in complex tasks and has publiclyshared its methodology. This provides poten…
Model Generalization: A Sharpness Aware Optimization Perspective
Jozef Marus Coldenhoff, Chengkun Li, Yurui Zhu
Sharpness-Aware Minimization (SAM) and adaptive sharpness-aware minimization (ASAM) aim to improve the model generalization. And in this project, we proposed three experiments to v…