Akash Srivastava
4 papers in the PaperMetrix corpus
Papers by this author
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Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
2018 · arXiv (Cornell University)
Uncertainty computation in deep learning is essential to design robust and reliable systems. Variational inference (VI) is a promising approach for such computation, but requires more effort to implement and execute compared to maximum-likelihood methods. …
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Post-processing Private Synthetic Data for Improving Utility on Selected Measures
2023 · arXiv (Cornell University)
Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of …
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LAB: Large-Scale Alignment for ChatBots
2024 · arXiv (Cornell University)
This work introduces LAB (Large-scale Alignment for chatBots), a novel methodology designed to overcome the scalability challenges in the instruction-tuning phase of large language model (LLM) training. Leveraging a taxonomy-guided synthetic data generation process and …
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Value Augmented Sampling for Language Model Alignment and Personalization
2024 · ArXiv.org
Aligning Large Language Models (LLMs) to cater to different human preferences, learning new skills, and unlearning harmful behavior is an important problem. Search-based methods, such as Best-of-N or Monte-Carlo Tree Search, are performant, but impractical …