3 citations · 3 across the 2 of their papers we have counts for
4 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…
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…
The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics
Christoph Leiter, Juri Opitz, Daniel Deutsch +3
With an increasing number of parameters and pre-training data, generative large language models (LLMs) have shown remarkable capabilities to solve tasks with minimal or no task-rel…
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…