7 citations · 16 across the 23 of their papers we have counts for
23 papers
NoC-Out: A Formally-verified Network-on-Chip Library for Rule-based Hardware Designs
Max Kurze, František Farka, Sebastian Ertel
The Network-on-Chip (NoC) is the communication backbone of any multiprocessor chip. A failure of the NoC has severe consequences for the whole system. Yet, no approach exists that…
RoboPIN: Grounded Embodied Reasoning via Pinned Chain-of-Thought
Yaoting Huang, Yifu Yuan, Linqi Han +6
Embodied reasoning requires models to perceive task-relevant objects and spaces in physical environments and maintain consistent visual grounding throughout multi-step reasoning. H…
LongCat-Flash-Thinking-2601 Technical Report
Meituan LongCat Team, Anchun Gui, Bei Li +162
We introduce LongCat-Flash-Thinking-2601, a 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model with superior agentic reasoning capability. LongCat-Flash-Thi…
Key Decision-Makers in Multi-Agent Debates: Who Holds the Power?
Qian Zhang, Yan Zheng, Jinyi Liu +2
Recent studies on LLM agent scaling have highlighted the potential of Multi-Agent Debate (MAD) to enhance reasoning abilities. However, the critical aspect of role allocation strat…
Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI
Fei Ni, Min Zhang, Pengyi Li +34
Embodied AI development significantly lags behind large foundation models due to three critical challenges: (1) lack of systematic understanding of core capabilities needed for Emb…
Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yaoting Huang +7
Generalization in embodied AI is hindered by the "seeing-to-doing gap," which stems from data scarcity and embodiment heterogeneity. To address this, we pioneer "pointing" as a uni…
Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model
Jing Liang, Hongyao Tang, Yi Ma +5
Reinforcement Learning (RL) has demonstrated its potential to improve the reasoning ability of Large Language Models (LLMs). One major limitation of most existing Reinforcement Fin…
Breaking Thought Patterns: A Multi-Dimensional Reasoning Framework for LLMs
Xintong Tang, Meiru Zhang, Shang Xiao +5
Large language models (LLMs) are often constrained by rigid reasoning processes, limiting their ability to generate creative and diverse responses. To address this, a novel framewo…
Reflex First, Reflect Later: Latency-Aware Embodied LLM Agents for Dynamic Response
Yangqing Zheng, Shunqi Mao, Dingxin Zhang +1
Large language models (LLMs) have substantially improved the planning capabilities of embodied agents, enabling their deployment in dynamic and safety-critical environments. Howeve…
From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yibin Chen +7
Achieving generalization in robotic manipulation remains a critical challenge, particularly for unseen scenarios and novel tasks. Current Vision-Language-Action (VLA) models, while…
DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering
Rong Cheng, Jinyi Liu, Yan Zheng +6
Multi-Hop Question Answering (MHQA) tasks permeate real-world applications, posing challenges in orchestrating multi-step reasoning across diverse knowledge domains. While existing…
From Chaos to Order: The Atomic Reasoner Framework for Fine-grained Reasoning in Large Language Models
Jinyi Liu, Yan Zheng, Rong Cheng +8
Recent advances in large language models (LLMs) have shown remarkable progress, yet their capacity for logical ``slow-thinking'' reasoning persists as a critical research frontier.…
AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI
Haiqin Cui, Yifu Yuan, Yan Zheng +1
Scaling Vision-Language-Action models for embodied manipulation demands large volumes of diverse manipulation data, yet the high cost of commercial mobile manipulators and teleoper…
CellAgent: An LLM-driven Multi-Agent Framework for Automated Single-cell Data Analysis
Yihang Xiao, Jinyi Liu, Yan Zheng +9
Single-cell RNA sequencing (scRNA-seq) data analysis is crucial for biological research, as it enables the precise characterization of cellular heterogeneity. However, manual manip…
MFE-ETP: A Comprehensive Evaluation Benchmark for Multi-modal Foundation Models on Embodied Task Planning
Min Zhang, Xian Fu, Jianye Hao +5
In recent years, Multi-modal Foundation Models (MFMs) and Embodied Artificial Intelligence (EAI) have been advancing side by side at an unprecedented pace. The integration of the t…
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
Zibin Dong, Yifu Yuan, Jianye Hao +4
Leveraging the powerful generative capability of diffusion models (DMs) to build decision-making agents has achieved extensive success. However, there is still a demand for an easy…
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Yifu Yuan, Jianye Hao, Yi Ma +6
Reinforcement Learning with Human Feedback (RLHF) has received significant attention for performing tasks without the need for costly manual reward design by aligning human prefere…
SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models
Yibin Chen, Yifu Yuan, Zeyu Zhang +6
Spreadsheets are ubiquitous across the World Wide Web, playing a critical role in enhancing work efficiency across various domains. Large language model (LLM) has been recently att…
Enhancing Robotic Manipulation with AI Feedback from Multimodal Large Language Models
Jinyi Liu, Yifu Yuan, Jianye Hao +4
Recently, there has been considerable attention towards leveraging large language models (LLMs) to enhance decision-making processes. However, aligning the natural language text in…
DiffuserLite: Towards Real-time Diffusion Planning
Zibin Dong, Jianye Hao, Yifu Yuan +4
Diffusion planning has been recognized as an effective decision-making paradigm in various domains. The capability of generating high-quality long-horizon trajectories makes it a p…
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments
Jinyi Liu, Zhi Wang, Yan Zheng +6
In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher un…
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye Hao +7
Aligning agent behaviors with diverse human preferences remains a challenging problem in reinforcement learning (RL), owing to the inherent abstractness and mutability of human pre…
ED2: Environment Dynamics Decomposition World Models for Continuous Control
Jianye Hao, Yifu Yuan, Cong Wang +1
Model-based reinforcement learning (MBRL) achieves significant sample efficiency in practice in comparison to model-free RL, but its performance is often limited by the existence o…