3 citations · 5 across the 7 of their papers we have counts for
9 papers
Diverse Thinking Schemata Elicit Better Reasoning in Large Language Models
Xinyue Liang, Yizhe Yang, Yu Bai +3
Large reasoning models (LRMs) have attracted increasing attention for their ability to solve complex mathematical problems by generating extended reasoning chains. In this work, we…
How Far Are We? Systematic Evaluation of LLMs vs. Human Experts in Mathematical Contest in Modeling
Yuhang Liu, Heyan Huang, Yizhe Yang +3
Large language models (LLMs) have achieved strong performance on reasoning benchmarks, yet their ability to solve real-world problems requiring end-to-end workflows remains unclear…
Unveiling and Addressing Pseudo Forgetting in Large Language Models
Huashan Sun, Yizhe Yang, Yinghao Li +2
Although substantial efforts have been made to mitigate catastrophic forgetting in continual learning, the intrinsic mechanisms are not well understood. In this work, we demonstrat…
PSPO*: An Effective Process-supervised Policy Optimization for Reasoning Alignment
Jiawei Li, Xinyue Liang, Junlong Zhang +3
Process supervision enhances the performance of large language models in reasoning tasks by providing feedback at each step of chain-of-thought reasoning. However, due to the lack…
Graph vs. Sequence: An Empirical Study on Knowledge Forms for Knowledge-Grounded Dialogue
Yizhe Yang, Heyan Huang, Yihang Liu +1
Knowledge-grounded dialogue is a task of generating an informative response based on both the dialogue history and external knowledge source. In general, there are two forms of kno…
PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer
Huashan Sun, Yixiao Wu, Yuhao Ye +4
Language style is necessary for AI systems to understand and generate diverse human language accurately. However, previous text style transfer primarily focused on sentence-level d…
MindLLM: Pre-training Lightweight Large Language Model from Scratch, Evaluations and Domain Applications
Yizhe Yang, Huashan Sun, Jiawei Li +5
Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. Wh…
Building Knowledge-Grounded Dialogue Systems with Graph-Based Semantic Modeling
Yizhe Yang, Heyan Huang, Yang Gao +1
The knowledge-grounded dialogue task aims to generate responses that convey information from given knowledge documents. However, it is a challenge for the current sequence-based mo…
Ask to Understand: Question Generation for Multi-hop Question Answering
Jiawei Li, Mucheng Ren, Yang Gao +1
Multi-hop Question Answering (QA) requires the machine to answer complex questions by finding scattering clues and reasoning from multiple documents. Graph Network (GN) and Questio…