6 citations · 7 across the 14 of their papers we have counts for
15 papers
EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning
Can Xie, Yuyi Zhou, Wen Yang +5
Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable exploration patterns embedded in i…
DialectS2S: End-to-End Speech Dialogue Modeling for Low-Resource Chinese Dialects
Yi Shu, Tianyu Peng, Yingzhuo Deng +5
Current end-to-end speech dialogue models are primarily optimized for mainstream languages and remain limited in low-resource dialect scenarios due to the scarcity of dialect speec…
TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment
Chong Li, Yingzhuo Deng, Wen Yang +2
Tokenization is a foundational step in the text process of Large Language Models (LLMs). Texts must be first tokenized into token IDs, which are then input to LLMs. Inefficient tok…
How Well Does Mathematical Reasoning Transfer Across Languages in English-Centric LLMs?
Wen Yang, Junhong Wu, Chong Li +2
Recent advances in Reinforcement Post-Training (RPT) have substantially improved the mathematical reasoning capabilities of large language models (LLMs), but it remains unclear how…
Teaching Vision-Language Models to Ask: Resolving Ambiguity in Visual Questions
Pu Jian, Donglei Yu, Wen Yang +2
In visual question answering (VQA) context, users often pose ambiguous questions to visual language models (VLMs) due to varying expression habits. Existing research addresses such…
OpenS2S: Advancing Fully Open-Source End-to-End Empathetic Large Speech Language Model
Chen Wang, Tianyu Peng, Wen Yang +8
Empathetic interaction is a cornerstone of human-machine communication, due to the need for understanding speech enriched with paralinguistic cues and generating emotional and expr…
KTAE: A Model-Free Algorithm to Key-Tokens Advantage Estimation in Mathematical Reasoning
Wei Sun, Wen Yang, Pu Jian +4
Recent advances have demonstrated that integrating reinforcement learning with rule-based rewards can significantly enhance the reasoning capabilities of large language models, eve…
Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference Alignment
Wen Yang, Junhong Wu, Chen Wang +2
Direct Preference Optimization (DPO) has become a prominent method for aligning Large Language Models (LLMs) with human preferences. While DPO has enabled significant progress in a…
Language hooks: a modular framework for augmenting LLM reasoning that decouples tool usage from the model and its prompt
Damien de Mijolla, Wen Yang, Philippa Duckett +2
Prompting and fine-tuning have emerged as two competing paradigms for augmenting language models with new capabilities, such as the use of tools. Prompting approaches are quick to…
ChineseWebText 2.0: Large-Scale High-quality Chinese Web Text with Multi-dimensional and fine-grained information
Wanyue Zhang, Ziyong Li, Wen Yang +5
During the development of large language models (LLMs), pre-training data play a critical role in shaping LLMs' capabilities. In recent years several large-scale and high-quality p…
Markov Chain of Thought for Efficient Mathematical Reasoning
Wen Yang, Minpeng Liao, Kai Fan
Chain of Thought (CoT) of multi-step benefits from the logical structure of the reasoning steps and task-specific actions, significantly enhancing the mathematical reasoning capabi…
Language Imbalance Driven Rewarding for Multilingual Self-improving
Wen Yang, Junhong Wu, Chen Wang +2
Large Language Models (LLMs) have achieved state-of-the-art performance across numerous tasks. However, these advancements have predominantly benefited "first-class" languages such…
PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation
Jing Luo, Longze Chen, Run Luo +12
While closed-source Large Language Models (LLMs) demonstrate strong mathematical problem-solving abilities, open-source models still face challenges with such tasks. To bridge this…
X-Instruction: Aligning Language Model in Low-resource Languages with Self-curated Cross-lingual Instructions
Chong Li, Wen Yang, Jiajun Zhang +3
Large language models respond well in high-resource languages like English but struggle in low-resource languages. It may arise from the lack of high-quality instruction following…
BigTranslate: Augmenting Large Language Models with Multilingual Translation Capability over 100 Languages
Wen Yang, Chong Li, Jiajun Zhang +1
Large language models (LLMs) demonstrate promising translation performance among various natural languages. However, many LLMs especially the open-sourced ones, such as BLOOM and L…