2 citations · 2 across the 11 of their papers we have counts for
12 papers
PMOPD: Task Ordering, Cycling, and Parameter-Update Subspace Protection in Multi-Teacher On-Policy Distillation
Youzhi Liu, Ruobing Zheng, Boyuan Tong +5
Multi-teacher on-policy distillation (MOPD) has emerged as a popular post-training paradigm for integrating specialized capabilities in frontier language models. Existing OPD resea…
Dual Tuning for Reasoning Efficacy-Driven Data Curation in Multimodal LLM Training
Ruobing Zheng, Tianqi Li, Jianing Li +3
Reasoning post-training improves Large Language Models (LLMs) on complex tasks such as mathematics and coding, but its benefits across diverse multimodal tasks remains uncertain. T…
Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation
Inclusion AI, :, Bowen Ma +73
We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…
HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses through Reasoning MLLMs
Zheng Qin, Ruobing Zheng, Yabing Wang +4
While Multimodal Large Language Models (MLLMs) show immense promise for achieving truly human-like interactions, progress is hindered by the lack of fine-grained evaluation framewo…
M2-Reasoning: Empowering MLLMs with Unified General and Spatial Reasoning
Inclusion AI, :, Fudong Wang +12
Recent advancements in Multimodal Large Language Models (MLLMs), particularly through Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced their reaso…
EchoMimicV3: 1.3B Parameters are All You Need for Unified Multi-Modal and Multi-Task Human Animation
Rang Meng, Yan Wang, Weipeng Wu +3
Recent work on human animation usually incorporates large-scale video models, thereby achieving more vivid performance. However, the practical use of such methods is hindered by th…
Versatile Multimodal Controls for Expressive Talking Human Animation
Zheng Qin, Ruobing Zheng, Yabing Wang +5
In filmmaking, directors typically allow actors to perform freely based on the script before providing specific guidance on how to present key actions. AI-generated content faces s…
LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis
Tianqi Li, Ruobing Zheng, Bonan Li +4
Despite significant progress in talking head synthesis since the introduction of Neural Radiance Fields (NeRF), visual artifacts and high training costs persist as major obstacles…
Ditto: Motion-Space Diffusion for Controllable Realtime Talking Head Synthesis
Tianqi Li, Ruobing Zheng, Minghui Yang +2
Recent advances in diffusion models have endowed talking head synthesis with subtle expressions and vivid head movements, but have also led to slow inference speed and insufficient…
Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Shuai Tan, Biao Gong, Xiang Wang +6
Character image animation, which generates high-quality videos from a reference image and target pose sequence, has seen significant progress in recent years. However, most existin…
StyleTokenizer: Defining Image Style by a Single Instance for Controlling Diffusion Models
Wen Li, Muyuan Fang, Cheng Zou +5
Despite the burst of innovative methods for controlling the diffusion process, effectively controlling image styles in text-to-image generation remains a challenging task. Many ada…
Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis
Zicheng Zhang, Ruobing Zheng, Ziwen Liu +7
Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences. These i…