2 citations · 8 across the 20 of their papers we have counts for
5 papers · 1 filter
Do LLMs Signal When They're Right? Evidence from Neuron Agreement
Kang Chen, Yaoning Wang, Kai Xiong +4
Large language models (LLMs) commonly boost reasoning via sample-evaluate-ensemble decoders, achieving label free gains without ground truth. However, prevailing strategies score c…
SciRerankBench: Benchmarking Rerankers Towards Scientific Retrieval-Augmented Generation with LLMs
Haotian Chen, Qingqing Long, Meng Xiao +6
Scientific literature question answering is a pivotal step towards new scientific discoveries. Recently, \textit{two-stage} retrieval-augmented generated large language models (RAG…
AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning
Zhong Zhang, Yaxi Lu, Yikun Fu +22
The recent progress of large language model agents has opened new possibilities for automating tasks through graphical user interfaces (GUIs), especially in mobile environments whe…
MiniCPM4: Ultra-Efficient LLMs on End Devices
MiniCPM Team, Chaojun Xiao, Yuxuan Li +80
This paper introduces MiniCPM4, a highly efficient large language model (LLM) designed explicitly for end-side devices. We achieve this efficiency through systematic innovation in…
ToLeaP: Rethinking Development of Tool Learning with Large Language Models
Haotian Chen, Zijun Song, Boye Niu +8
Tool learning, which enables large language models (LLMs) to utilize external tools effectively, has garnered increasing attention for its potential to revolutionize productivity a…