6 citations · 6 across the 8 of their papers we have counts for
9 papers
ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization
Guoxin Chen, Jing Wu, Xinjie Chen +6
Autoformalization, which translates natural language mathematics into machine-verifiable formal statements, is critical for using formal mathematical reasoning to solve math proble…
From Data-Centric to Sample-Centric: Enhancing LLM Reasoning via Progressive Optimization
Xinjie Chen, Minpeng Liao, Guoxin Chen +4
Reinforcement learning with verifiable rewards (RLVR) has recently advanced the reasoning capabilities of large language models (LLMs). While prior work has emphasized algorithmic…
LLMs Can Achieve High-quality Simultaneous Machine Translation as Efficiently as Offline
Biao Fu, Minpeng Liao, Kai Fan +4
When the complete source sentence is provided, Large Language Models (LLMs) perform excellently in offline machine translation even with a simple prompt "Translate the following se…
Efficient and Adaptive Simultaneous Speech Translation with Fully Unidirectional Architecture
Biao Fu, Donglei Yu, Minpeng Liao +5
Simultaneous speech translation (SimulST) produces translations incrementally while processing partial speech input. Although large language models (LLMs) have shown strong capabil…
Step-level Value Preference Optimization for Mathematical Reasoning
Guoxin Chen, Minpeng Liao, Chengxi Li +1
Direct Preference Optimization (DPO) using an implicit reward model has proven to be an effective alternative to reinforcement learning from human feedback (RLHF) for fine-tuning p…
AlphaMath Almost Zero: Process Supervision without Process
Guoxin Chen, Minpeng Liao, Chengxi Li +1
Although recent advancements in large language models (LLMs) have significantly improved their performance on various tasks, they still face challenges with complex and symbolic mu…
MARIO Eval: Evaluate Your Math LLM with your Math LLM--A mathematical dataset evaluation toolkit
Boning Zhang, Chengxi Li, Kai Fan
Large language models (LLMs) have been explored in a variety of reasoning tasks including solving of mathematical problems. Each math dataset typically includes its own specially d…
MARIO: MAth Reasoning with code Interpreter Output -- A Reproducible Pipeline
Minpeng Liao, Wei Luo, Chengxi Li +2
Large language models (LLMs) have seen considerable advancements in natural language understanding tasks, yet there remains a gap to bridge before attaining true artificial general…
A Self-Explainable Stylish Image Captioning Framework via Multi-References
Chengxi Li, Brent Harrison
In this paper, we propose to build a stylish image captioning model through a Multi-style Multi modality mechanism (2M). We demonstrate that with 2M, we can build an effective styl…