80 citations · 112 across the 13 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.…
Self-Supervised Audio-and-Text Pre-training with Extremely Low-Resource Parallel Data
Yu Kang, Tianqiao Liu, Hang Li +2
Multimodal pre-training for audio-and-text has recently been proved to be effective and has significantly improved the performance of many downstream speech understanding tasks. Ho…
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations
Hang Li, Yu Kang, Tianqiao Liu +2
Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms. However, these models are facing challenges of overfitting with li…
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao +6
Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. SC questions are widely…
Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations
Tianqiao Liu, Qiang Fang, Wenbiao Ding +3
There is an increasing interest in the use of mathematical word problem (MWP) generation in educational assessment. Different from standard natural question generation, MWP generat…
Automatic Short Answer Grading via Multiway Attention Networks
Tiaoqiao Liu, Wenbiao Ding, Zhiwei Wang +3
Automatic short answer grading (ASAG), which autonomously score student answers according to reference answers, provides a cost-effective and consistent approach to teaching profes…
Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education
Wenbiao Ding, Guowei Xu, Tianqiao Liu +7
Spoken language proficiency is critically important for children's growth and personal development. Due to the limited and imbalanced educational resources in China, elementary stu…
Recommender Systems with Heterogeneous Side Information
Tianqiao Liu, Zhiwei Wang, Jiliang Tang +3
In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items. Such information is typically heterogeneou…