10 citations · 11 across the 8 of their papers we have counts for
9 papers
PrimeScientist: Strategic Allocation of Research Effort in Autonomous Research
Xinle Yu, Fan Bai, Kaiser Sun +5
Autonomous research agents aim to automate scientific workflows, from proposing ideas to conducting experiments and analyzing results. Yet current AI and research agents can propos…
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights
Zhen Wang, Fan Bai, Zhongyan Luo +9
Autonomous agents powered by large language models (LLMs) promise to accelerate scientific discovery end-to-end, but rigorously evaluating their capacity for verifiable discovery r…
Ability Transfer and Recovery via Modularized Parameters Localization
Songyao Jin, Kun Zhou, Wenqi Li +2
Large language models can be continually pre-trained or fine-tuned to improve performance in specific domains, languages, or skills, but this specialization often degrades other ca…
VC-Agent: An Interactive Agent for Customized Video Dataset Collection
Yidan Zhang, Mutian Xu, Yiming Hao +6
Facing scaling laws, video data from the internet becomes increasingly important. However, collecting extensive videos that meet specific needs is extremely labor-intensive and tim…
From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs
Jiliang Ni, Jiachen Pu, Zhongyi Yang +7
Large Language Models (LLMs) have significantly advanced artificial intelligence by optimizing traditional Natural Language Processing (NLP) workflows, facilitating their integrati…
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue Wang, Huan Li +6
Large Language Models (LLMs) have significantly advanced natural language processing with exceptional task generalization capabilities. Low-Rank Adaption (LoRA) offers a cost-effec…
RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
Zhensheng Wang, Wenmian Yang, Kun Zhou +2
The real estate market relies heavily on structured data, such as property details, market trends, and price fluctuations. However, the lack of specialized Tabular Question Answeri…
Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMs
Bilgehan Sel, Priya Shanmugasundaram, Mohammad Kachuee +3
Large Language Models (LLMs) have shown remarkable capabilities in tasks such as summarization, arithmetic reasoning, and question answering. However, they encounter significant ch…
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Qi Chen, Xiubo Geng, Corby Rosset +28
Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-s…