ImPaKT: A Dataset for Open-Schema Knowledge Base Construction von Vilnis, Luke, Fisher, Zach, Kanagal, Bhargav, Murray, Patrick, Sanghai, Sumit

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Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models von Vilnis, Luke, Zemlyanskiy, Yury, Murray, Patrick, Passos, Alexandre, Sanghai, Sumit

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MEMORY-VQ: Compression for Tractable Internet-Scale Memory von Zemlyanskiy, Yury, de Jong, Michiel, Vilnis, Luke, Ontañón, Santiago, Cohen, William W, Sanghai, Sumit, Ainslie, Joshua

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Word Representations via Gaussian Embedding von Vilnis, Luke, McCallum, Andrew

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Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models von Luke Vilnis, Zemlyanskiy, Yury, Murray, Patrick, Passos, Alexandre, Sanghai, Sumit

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Improved Representation Learning for Predicting Commonsense Ontologies von Li, Xiang, Vilnis, Luke, McCallum, Andrew

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CodeGemma: Open Code Models Based on Gemma von CodeGemma Team, Zhao, Heri, Hui, Jeffrey, Howland, Joshua, Nguyen, Nam, Zuo, Siqi, Hu, Andrea, Choquette-Choo, Christopher A, Shen, Jingyue, Kelley, Joe, Bansal, Kshitij, Vilnis, Luke, Wirth, Mateo, Michel, Paul, Choy, Peter, Joshi, Pratik, Kumar, Ravin, Hashmi, Sarmad, Agrawal, Shubham, Gong, Zhitao, Fine, Jane, Warkentin, Tris, Hartman, Ale Jakse, Ni, Bin, Korevec, Kathy, Schaefer, Kelly, Huffman, Scott

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Improving Local Identifiability in Probabilistic Box Embeddings von Dasgupta, Shib Sankar, Boratko, Michael, Zhang, Dongxu, Vilnis, Luke, Li, Xiang Lorraine, McCallum, Andrew

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ImPaKT: A Dataset for Open-Schema Knowledge Base Construction von Luke Vilnis, Fisher, Zach, Kanagal, Bhargav, Murray, Patrick, Sanghai, Sumit

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Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking von Murty, Shikhar, Verga, Patrick, Vilnis, Luke, Radovanovic, Irena, McCallum, Andrew

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Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures von Vilnis, Luke, Li, Xiang, Murty, Shikhar, McCallum, Andrew

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MEMORY-VQ: Compression for Tractable Internet-Scale Memory von Zemlyanskiy, Yury, de Jong, Michiel, Luke Vilnis, Ontañón, Santiago, Cohen, William W, Sanghai, Sumit, Ainslie, Joshua

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Finer Grained Entity Typing with TypeNet von Murty, Shikhar, Verga, Patrick, Vilnis, Luke, McCallum, Andrew

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Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection von Chang, Haw-Shiuan, Wang, ZiYun, Vilnis, Luke, McCallum, Andrew

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Embedded-State Latent Conditional Random Fields for Sequence Labeling von Thai, Dung, Ramesh, Sree Harsha, Murty, Shikhar, Vilnis, Luke, McCallum, Andrew

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Word Representations via Gaussian Embedding von Luke Vilnis, McCallum, Andrew

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Training for Fast Sequential Prediction Using Dynamic Feature Selection von Strubell, Emma, Vilnis, Luke, McCallum, Andrew

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Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning von Das, Rajarshi, Dhuliawala, Shehzaad, Zaheer, Manzil, Vilnis, Luke, Durugkar, Ishan, Krishnamurthy, Akshay, Smola, Alex, McCallum, Andrew

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Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling von Thai, Dung, Murty, Shikhar, Bansal, Trapit, Vilnis, Luke, Belanger, David, McCallum, Andrew

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Improved Representation Learning for Predicting Commonsense Ontologies von Li, Xiang, Luke Vilnis, McCallum, Andrew

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