1 citations · 1 across the 4 of their papers we have counts for
4 papers
Orchestrating Tokens and Sequences: Dynamic Hybrid Policy Optimization for RLVR
Zijun Min, Bingshuai Liu, Ante Wang +4
Reinforcement Learning with Verifiable Rewards (RLVR) offers a promising framework for optimizing large language models in reasoning tasks. However, existing RLVR algorithms focus…
SPEC-RL: Accelerating On-Policy Reinforcement Learning with Speculative Rollouts
Bingshuai Liu, Ante Wang, Zijun Min +7
Large Language Models (LLMs) increasingly rely on reinforcement learning with verifiable rewards (RLVR) to elicit reliable chain-of-thought reasoning. However, the training process…
Exploring Optimal Transport-Based Multi-Grained Alignments for Text-Molecule Retrieval
Zijun Min, Bingshuai Liu, Liang Zhang +4
The field of bioinformatics has seen significant progress, making the cross-modal text-molecule retrieval task increasingly vital. This task focuses on accurately retrieving molecu…
Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models
Bingshuai Liu, Chenyang Lyu, Zijun Min +3
The advancement of Large Language Models (LLMs) has brought substantial attention to the Chain of Thought (CoT) approach, primarily due to its ability to enhance the capability of…