80 citations · 90 across the 10 of their papers we have counts for
13 papers
From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training
Tianqiao Liu, Xueyi Li, Hao Wang +4
Recent advances in large language models (LLMs) have attracted significant interest in extending their capabilities to multimodal scenarios, particularly for speech-to-speech conve…
Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages
Zui Chen, Tianqiao Liu, Mi Tian +3
Mathematical reasoning remains a challenging area for large language models (LLMs), prompting the development of math-specific LLMs such as LLEMMA, DeepSeekMath, and Qwen2-Math, am…
What Are Step-Level Reward Models Rewarding? Counterintuitive Findings from MCTS-Boosted Mathematical Reasoning
Yiran Ma, Zui Chen, Tianqiao Liu +4
Step-level reward models (SRMs) can significantly enhance mathematical reasoning performance through process supervision or step-level preference alignment based on reinforcement l…
Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding
Tianqiao Liu, Zui Chen, Zitao Liu +2
Large language models (LLMs) have demonstrated remarkable capabilities in tasks requiring reasoning and multi-step problem-solving through the use of chain-of-thought (CoT) prompti…
Optimal Transport for Treatment Effect Estimation
Hao Wang, Zhichao Chen, Jiajun Fan +7
Estimating conditional average treatment effect from observational data is highly challenging due to the existence of treatment selection bias. Prevalent methods mitigate this issu…
ESCM: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation
Hao Wang, Tai-Wei Chang, Tianqiao Liu +5
Accurate estimation of post-click conversion rate is critical for building recommender systems, which has long been confronted with sample selection bias and data sparsity issues.…