72 citations · 492 across the 44 of their papers we have counts for
12 papers · 1 filter
FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documents
Yilun Zhao, Yitao Long, Yuru Jiang +7
We introduce FinDVer, a comprehensive benchmark specifically designed to evaluate the explainable claim verification capabilities of LLMs in the context of understanding and analyz…
Step-Back Profiling: Distilling User History for Personalized Scientific Writing
Xiangru Tang, Xingyao Zhang, Yanjun Shao +6
Large language models (LLM) excel at a variety of natural language processing tasks, yet they struggle to generate personalized content for individuals, particularly in real-world…
OpenHands: An Open Platform for AI Software Developers as Generalist Agents
Xingyao Wang, Boxuan Li, Yufan Song +21
Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways. At the same…
Data Preparation for Deep Learning based Code Smell Detection: A Systematic Literature Review
Fengji Zhang, Zexian Zhang, Jacky Wai Keung +4
Code Smell Detection (CSD) plays a crucial role in improving software quality and maintainability. And Deep Learning (DL) techniques have emerged as a promising approach for CSD du…
Unveiling the Spectrum of Data Contamination in Language Models: A Survey from Detection to Remediation
Chunyuan Deng, Yilun Zhao, Yuzhao Heng +4
Data contamination has garnered increased attention in the era of large language models (LLMs) due to the reliance on extensive internet-derived training corpora. The issue of trai…
Lessons from the Trenches on Reproducible Evaluation of Language Models
Stella Biderman, Hailey Schoelkopf, Lintang Sutawika +27
Reliable evaluation of language models (LMs) remains an open challenge. Re- searchers and engineers face methodological issues such as the sensitivity of models to evaluation setup…
MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
Chunyuan Deng, Xiangru Tang, Yilun Zhao +5
Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without s…
StarCoder 2 and The Stack v2: The Next Generation
Anton Lozhkov, Raymond Li, Loubna Ben Allal +63
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…
Data Interpreter: An LLM Agent For Data Science
Sirui Hong, Yizhang Lin, Bang Liu +24
Large Language Model (LLM)-based agents have shown effectiveness across many applications. However, their use in data science scenarios requiring solving long-term interconnected t…
A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation
Xiangru Tang, Howard Dai, Elizabeth Knight +4
Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative mod…
Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy
Xiangru Tang, Qiao Jin, Kunlun Zhu +10
AI scientists powered by large language models have demonstrated substantial promise in autonomously conducting experiments and facilitating scientific discoveries across various d…
Weaver: Foundation Models for Creative Writing
Tiannan Wang, Jiamin Chen, Qingrui Jia +43
This work introduces Weaver, our first family of large language models (LLMs) dedicated to content creation. Weaver is pre-trained on a carefully selected corpus that focuses on im…