29 citations · 49 across the 7 of their papers we have counts for
7 papers
Quantifying Empirical Compute-Supervision Tradeoffs in RLVR
Ryo Mitsuhashi, Patrick Chen, Isabelle Tseng +2
Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training language models, but in practice, verifiers are rarely perfect. Recent theore…
ELIAS: End-to-End Learning to Index and Search in Large Output Spaces
Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu +2
Extreme multi-label classification (XMC) is a popular framework for solving many real-world problems that require accurate prediction from a very large number of potential output c…
FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search
Patrick H. Chen, Chang Wei-cheng, Yu Hsiang-fu +2
Approximate K-Nearest Neighbor Search (AKNNS) has now become ubiquitous in modern applications, for example, as a fast search procedure with two tower deep learning models. Graph-b…
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Minhao Cheng, Simranjit Singh, Patrick Chen +3
We study the most practical problem setup for evaluating adversarial robustness of a machine learning system with limited access: the hard-label black-box attack setting for genera…
Efficient Contextual Representation Learning Without Softmax Layer
Liunian Harold Li, Patrick H. Chen, Cho-Jui Hsieh +1
Contextual representation models have achieved great success in improving various downstream tasks. However, these language-model-based encoders are difficult to train due to the l…
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks
Patrick H. Chen, Si Si, Sanjiv Kumar +2
Neural language models have been widely used in various NLP tasks, including machine translation, next word prediction and conversational agents. However, it is challenging to depl…
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Patrick H. Chen, Si Si, Yang Li +2
Model compression is essential for serving large deep neural nets on devices with limited resources or applications that require real-time responses. As a case study, a state-of-th…