1 citations · 1 across the 11 of their papers we have counts for
12 papers
A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching
Feiyang Fu, Hehe Fan
Discrete flow matching (DFM) provides a principled framework for generative modeling on discrete state spaces via continuous-time Markov chain dynamics. In practice, sampling for D…
Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe
Wenjin Hou, Shangpin Peng, Weinong Wang +13
On-policy distillation (OPD) has recently emerged as an effective post-training paradigm for consolidating the capabilities of specialized expert models into a single student model…
Super Research: Answering Highly Complex Questions with Large Language Models through Super Deep and Super Wide Research
Yubo Dong, Nianhao You, Yuxuan Hou +5
While Large Language Models (LLMs) have demonstrated proficiency in Deep Research or Wide Search, their capacity to solve highly complex questions-those requiring long-horizon plan…
Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL
Yixiao Zhou, Yang Li, Dongzhou Cheng +2
Reinforcement Learning from Verifiable Rewards (RLVR) trains large language models (LLMs) from sampled trajectories, making decoding strategy a core component of learning rather th…
Seeing Is Believing? A Benchmark for Multimodal Large Language Models on Visual Illusions and Anomalies
Wenjin Hou, Wei Liu, Han Hu +3
Multimodal Large Language Models (MLLMs) have shown remarkable proficiency on general-purpose vision-language benchmarks, reaching or even exceeding human-level performance. Howeve…
ITS3D: Inference-Time Scaling for Text-Guided 3D Diffusion Models
Zhenglin Zhou, Fan Ma, Xiaobo Xia +3
We explore inference-time scaling in text-guided 3D diffusion models to enhance generative quality without additional training. To this end, we introduce ITS3D, a framework that fo…
AnchorFlow: Training-Free 3D Editing via Latent Anchor-Aligned Flows
Zhenglin Zhou, Fan Ma, Chengzhuo Gui +4
Training-free 3D editing aims to modify 3D shapes based on human instructions without model finetuning. It plays a crucial role in 3D content creation. However, existing approaches…
Enhancing Large Language Models through Structured Reasoning
Yubo Dong, Hehe Fan
Recent Large Language Models (LLMs) have significantly advanced natural language processing and automated decision-making. However, these models still encounter difficulties when p…
Zero-1-to-A: Zero-Shot One Image to Animatable Head Avatars Using Video Diffusion
Zhenglin Zhou, Fan Ma, Hehe Fan +1
Animatable head avatar generation typically requires extensive data for training. To reduce the data requirements, a natural solution is to leverage existing data-free static avata…
DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization
Zhenglin Zhou, Xiaobo Xia, Fan Ma +3
Text-to-3D generation automates 3D content creation from textual descriptions, which offers transformative potential across various fields. However, existing methods often struggle…
TV-Dialogue: Crafting Theme-Aware Video Dialogues with Immersive Interaction
Sai Wang, Fan Ma, Xinyi Li +2
Recent advancements in LLMs have accelerated the development of dialogue generation across text and images, yet video-based dialogue generation remains underexplored and presents u…
InfiniDreamer: Arbitrarily Long Human Motion Generation via Segment Score Distillation
Wenjie Zhuo, Fan Ma, Hehe Fan
We present InfiniDreamer, a novel framework for arbitrarily long human motion generation. InfiniDreamer addresses the limitations of current motion generation methods, which are ty…