24 citations · 64 across the 10 of their papers we have counts for
10 papers
Olmo 3
Team Olmo, :, Allyson Ettinger +66
We introduce Olmo 3, a family of state-of-the-art, fully-open language models at the 7B and 32B parameter scales. Olmo 3 model construction targets long-context reasoning, function…
Spurious Rewards: Rethinking Training Signals in RLVR
Rulin Shao, Shuyue Stella Li, Rui Xin +11
We show that reinforcement learning with verifiable rewards (RLVR) can elicit strong mathematical reasoning in certain language models even with spurious rewards that have little,…
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…
Optimal Sparse Survival Trees
Rui Zhang, Rui Xin, Margo Seltzer +1
Interpretability is crucial for doctors, hospitals, pharmaceutical companies and biotechnology corporations to analyze and make decisions for high stakes problems that involve huma…
Quantifying User Password Exposure to Third-Party CDNs
Rui Xin, Shihan Lin, Xiaowei Yang
Web services commonly employ Content Distribution Networks (CDNs) for performance and security. As web traffic is becoming 100% HTTPS, more and more websites allow CDNs to terminat…
Optimal Sparse Regression Trees
Rui Zhang, Rui Xin, Margo Seltzer +1
Regression trees are one of the oldest forms of AI models, and their predictions can be made without a calculator, which makes them broadly useful, particularly for high-stakes app…
Exploring the Whole Rashomon Set of Sparse Decision Trees
Rui Xin, Chudi Zhong, Zhi Chen +3
In any given machine learning problem, there may be many models that could explain the data almost equally well. However, most learning algorithms return only one of these models,…
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization
Zijie J. Wang, Chudi Zhong, Rui Xin +5
Given thousands of equally accurate machine learning (ML) models, how can users choose among them? A recent ML technique enables domain experts and data scientists to generate a co…
InviCloak: An End-to-End Approach to Privacy and Performance in Web Content Distribution
Shihan Lin, Rui Xin, Aayush Goel +1
In today's web ecosystem, a website that uses a Content Delivery Network (CDN) shares its Transport Layer Security (TLS) private key or session key with the CDN. In this paper, we…
Multitask Learning for Citation Purpose Classification
Alex Oesterling, Angikar Ghosal, Haoyang Yu +4
We present our entry into the 2021 3C Shared Task Citation Context Classification based on Purpose competition. The goal of the competition is to classify a citation in a scientifi…