29 citations · 31 across the 8 of their papers we have counts for
8 papers
From Events to Trending: A Multi-Stage Hotspots Detection Method Based on Generative Query Indexing
Kaichun Wang, Yanguang Chen, Ting Zhang +7
LLM-based conversational systems have become a popular gateway for information access, yet most existing chatbots struggle to handle news-related trending queries effectively. To i…
AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
Jinghang Shi, Xiaoyu Tang, Yang Huang +4
Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…
Improved Algorithms for Differentially Private Language Model Alignment
Keyu Chen, Hao Tang, Qinglin Liu +1
Language model alignment is crucial for ensuring that large language models (LLMs) align with human preferences, yet it often involves sensitive user data, raising significant priv…
Parameter-Efficient Fine-Tuning With Adapters
Keyu Chen, Yuan Pang, Zi Yang
In the arena of language model fine-tuning, the traditional approaches, such as Domain-Adaptive Pretraining (DAPT) and Task-Adaptive Pretraining (TAPT), although effective, but com…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset
Jiantao Qiu, Haijun Lv, Zhenjiang Jin +23
This paper presents WanJuan-CC, a safe and high-quality open-sourced English webtext dataset derived from Common Crawl data. The study addresses the challenges of constructing larg…
F-Eval: Assessing Fundamental Abilities with Refined Evaluation Methods
Yu Sun, Keyu Chen, Shujie Wang +6
Large language models (LLMs) garner significant attention for their unprecedented performance, leading to an increasing number of researches evaluating LLMs. However, these evaluat…
CoLLiE: Collaborative Training of Large Language Models in an Efficient Way
Kai Lv, Shuo Zhang, Tianle Gu +11
Large language models (LLMs) are increasingly pivotal in a wide range of natural language processing tasks. Access to pre-trained models, courtesy of the open-source community, has…