2 citations · 2 across the 2 of their papers we have counts for
4 papers
Short-Path Prompting in LLMs: Analyzing Reasoning Instability and Solutions for Robust Performance
Zuoli Tang, Junjie Ou, Kaiqin Hu +6
Recent years have witnessed significant progress in large language models' (LLMs) reasoning, which is largely due to the chain-of-thought (CoT) approaches, allowing models to gener…
DAgent: A Relational Database-Driven Data Analysis Report Generation Agent
Wenyi Xu, Yuren Mao, Xiaolu Zhang +4
Relational database-driven data analysis (RDB-DA) report generation, which aims to generate data analysis reports after querying relational databases, has been widely applied in fi…
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs
Ling Team, Binwei Zeng, Chao Huang +71
In this technical report, we tackle the challenges of training large-scale Mixture of Experts (MoE) models, focusing on overcoming cost inefficiency and resource limitations preval…
BOSE: A Systematic Evaluation Method Optimized for Base Models
Hongzhi Luan, Changxin Tian, Zhaoxin Huan +4
This paper poses two critical issues in evaluating base models (without post-training): (1) Unstable evaluation during training: in the early stages of pre-training, the models lac…