Kilian Q. Weinberger
7 papers in the PaperMetrix corpus
Papers by this author
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Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision
2021 · International Conference on Machine Learning
Low-precision training has become a popular approach to reduce compute requirements, memory footprint, and energy consumption in supervised learning. In contrast, this promising approach has not yet enjoyed similarly widespread adoption within the reinforcement learning …
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Orchestrating LLMs with Different Personalizations
2024 · arXiv (Cornell University)
This paper presents a novel approach to aligning large language models (LLMs) with individual human preferences, sometimes referred to as Reinforcement Learning from \textit{Personalized} Human Feedback (RLPHF). Given stated preferences along multiple dimensions, such as …
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Supervised word mover's distance
2016 · PolyPublie (École Polytechnique de Montréal)
Recently, a new document metric called the word mover’s distance (WMD) has been proposed with unprecedented results on kNN-based document classification. The WMD elevates high-quality word embeddings to a document metric by formulating the distance …
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BERTScore: Evaluating Text Generation with BERT
2019 · arXiv (Cornell University)
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to common metrics, BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. However, instead …
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Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification
2018 · Transactions of the Association for Computational Linguistics
In recent years great success has been achieved in sentiment classification for English, thanks in part to the availability of copious annotated resources. Unfortunately, most languages do not enjoy such an abundance of labeled data. …
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BERTScore: Evaluating Text Generation with BERT
2020 · arXiv (Cornell University)
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to common metrics, BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. However, instead …
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From Word Embeddings To Document Distances
2015 · PolyPublie (École Polytechnique de Montréal)
We present the Word Mover's Distance (WMD), a novel distance function between text documents. Our work is based on recent results in word embeddings that learn semantically meaningful representations for words from local cooccurrences in …