Data Transmission in Mobile Edge Networks: Whether and Where to Compress? von Ren, Jinke, Ruan, Yangjun, Yu, Guanding

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Observational Scaling Laws and the Predictability of Language Model Performance von Ruan, Yangjun, Maddison, Chris J, Hashimoto, Tatsunori

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Graph-based Uncertainty Metrics for Long-form Language Model Outputs von Jiang, Mingjian, Ruan, Yangjun, Sattigeri, Prasanna, Roukos, Salim, Hashimoto, Tatsunori

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Optimal Representations for Covariate Shift von Ruan, Yangjun, Dubois, Yann, Maddison, Chris J

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Observational Scaling Laws and the Predictability of Language Model Performance von Ruan, Yangjun, Maddison, Chris J, Hashimoto, Tatsunori

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APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts von Dong, Honghua, Su, Qidong, Gao, Yubo, Li, Zhaoyu, Ruan, Yangjun, Pekhimenko, Gennady, Maddison, Chris J, Si, Xujie

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Weighted Ensemble Self-Supervised Learning von Ruan, Yangjun, Singh, Saurabh, Morningstar, Warren, Alemi, Alexander A, Ioffe, Sergey, Fischer, Ian, Dillon, Joshua V

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Identifying the Risks of LM Agents with an LM-Emulated Sandbox von Ruan, Yangjun, Dong, Honghua, Wang, Andrew, Pitis, Silviu, Zhou, Yongchao, Ba, Jimmy, Dubois, Yann, Maddison, Chris J, Hashimoto, Tatsunori

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Graph-based Uncertainty Metrics for Long-form Language Model Outputs von Jiang, Mingjian, Ruan, Yangjun, Sattigeri, Prasanna, Roukos, Salim, Hashimoto, Tatsunori

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Augment with Care: Contrastive Learning for Combinatorial Problems von Duan, Haonan, Vaezipoor, Pashootan, Paulus, Max B, Ruan, Yangjun, Maddison, Chris J

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Optimal Representations for Covariate Shift von Ruan, Yangjun, Dubois, Yann, Maddison, Chris J

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Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding von Ruan, Yangjun, Ullrich, Karen, Severo, Daniel, Townsend, James, Khisti, Ashish, Doucet, Arnaud, Makhzani, Alireza, Maddison, Chris J

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Learning to Learn by Zeroth-Order Oracle von Ruan, Yangjun, Xiong, Yuanhao, Reddi, Sashank, Kumar, Sanjiv, Hsieh, Cho-Jui

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APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts von Dong, Honghua, Su, Qidong, Gao, Yubo, Li, Zhaoyu, Ruan, Yangjun, Pekhimenko, Gennady, Maddison, Chris J, Si, Xujie

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Identifying the Risks of LM Agents with an LM-Emulated Sandbox von Ruan, Yangjun, Dong, Honghua, Wang, Andrew, Pitis, Silviu, Zhou, Yongchao, Ba, Jimmy, Dubois, Yann, Maddison, Chris J, Hashimoto, Tatsunori

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FastSpeech: Fast, Robust and Controllable Text to Speech von Ren, Yi, Ruan, Yangjun, Tan, Xu, Qin, Tao, Zhao, Sheng, Zhao, Zhou, Liu, Tie-Yan

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Weighted Ensemble Self-Supervised Learning von Ruan, Yangjun, Singh, Saurabh, Morningstar, Warren, Alemi, Alexander A, Ioffe, Sergey, Fischer, Ian, Dillon, Joshua V

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Augment with Care: Contrastive Learning for Combinatorial Problems von Duan, Haonan, Vaezipoor, Pashootan, Paulus, Max B, Ruan, Yangjun, Maddison, Chris J

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Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding von Ruan, Yangjun, Ullrich, Karen, Severo, Daniel, Townsend, James, Khisti, Ashish, Doucet, Arnaud, Makhzani, Alireza, Maddison, Chris J

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Learning to Learn by Zeroth-Order Oracle von Ruan, Yangjun, Xiong, Yuanhao, Reddi, Sashank, Kumar, Sanjiv, Cho-Jui Hsieh

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