1 citations · 1 across the 6 of their papers we have counts for
8 papers
CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness
Dongjie Cheng, Ruifeng Yuan, Ran Wei +3
As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images sho…
AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
Dongjie Cheng, Ruifeng Yuan, Yongqi Li +5
Real-world perception and interaction are inherently multimodal, encompassing not only language but also vision and speech, which motivates the development of "Omni" MLLMs that sup…
SCALE: Selective Resource Allocation for Overcoming Performance Bottlenecks in Mathematical Test-time Scaling
Yang Xiao, Chunpu Xu, Ruifeng Yuan +3
Test-time compute scaling has emerged as a powerful paradigm for enhancing mathematical reasoning in large language models (LLMs) by allocating additional computational resources d…
LIMOPro: Reasoning Refinement for Efficient and Effective Test-time Scaling
Yang Xiao, Jiashuo Wang, Ruifeng Yuan +4
Large language models (LLMs) have demonstrated remarkable reasoning capabilities through test-time scaling approaches, particularly when fine-tuned with chain-of-thought (CoT) data…
Exploring Training and Inference Scaling Laws in Generative Retrieval
Hongru Cai, Yongqi Li, Ruifeng Yuan +4
Generative retrieval reformulates retrieval as an autoregressive generation task, where large language models (LLMs) generate target documents directly from a query. As a novel par…
Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization
Shichao Sun, Ruifeng Yuan, Ziqiang Cao +2
Large language models (LLMs) have demonstrated the capacity to improve summary quality by mirroring a human-like iterative process of critique and refinement starting from the init…
The Critique of Critique
Shichao Sun, Junlong Li, Weizhe Yuan +3
Critique, as a natural language description for assessing the quality of model-generated content, has played a vital role in the training, evaluation, and refinement of LLMs. Howev…
Personalized Large Language Model Assistant with Evolving Conditional Memory
Ruifeng Yuan, Shichao Sun, Yongqi Li +3
With the rapid development of large language models, AI assistants like ChatGPT have become increasingly integrated into people's works and lives but are limited in personalized se…