2 citations · 3 across the 11 of their papers we have counts for
7 papers · 1 filter
Training-Free On-Policy Distillation
Bangji Yang, Jiajun Fan, Zhaoyu Zhu +2
On-policy distillation consolidates specialist models into one student at the price of rollouts, teacher passes and gradient steps for every teacher. We show that the consolidation…
: Spectral Null-Space Swap Makes Reasoning Models Efficient
Hongbo Ma, Sansheng Cao, Jiajun Fan +2
LLMs trained with Chain-of-thought excel in reasoning capability, but often come with excessive token cost. We find that the core of reasoning capacity lies in the Thinking model's…
Batched Contextual Reinforcement: A Task-Scaling Law for Efficient Reasoning
Bangji Yang, Hongbo Ma, Jiajun Fan +1
Large Language Models employing Chain-of-Thought reasoning achieve strong performance but suffer from excessive token consumption that inflates inference costs. Existing efficiency…
Incentivizing Consistent, Effective and Scalable Reasoning Capability in Audio LLMs via Reasoning Process Rewards
Jiajun Fan, Roger Ren, Jingyuan Li +6
The role of reasoning in Audio Large Language Models remains widely underexplored, as introducing a reasoning process often degrades rather than improves performance during inferen…
ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning
Ziwen Wang, Jiajun Fan, Ruihan Guo +3
Protein generative models have shown remarkable promise in protein design, yet their success rates remain constrained by reliance on curated sequence-structure datasets and by misa…
Variational Supervised Contrastive Learning
Ziwen Wang, Jiajun Fan, Thao Nguyen +2
Contrastive learning has proven to be highly efficient and adaptable in shaping representation spaces across diverse modalities by pulling similar samples together and pushing diss…
FARM: Enhancing Molecular Representations with Functional Group Awareness
Thao Nguyen, Kuan-Hao Huang, Ge Liu +3
We introduce Functional Group-Aware Representations for Small Molecules (FARM), a novel foundation model designed to bridge the gap between SMILES, natural language, and molecular…