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nlp:seq2seq

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nlp:seq2seq [2024/11/17 20:46] – [Decoding Strategies] jmflanignlp:seq2seq [2025/05/29 07:15] (current) – [Decoding Strategies] jmflanig
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     * [[https://arxiv.org/pdf/2109.05093.pdf|Scholak et al 2021 - PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models]]     * [[https://arxiv.org/pdf/2109.05093.pdf|Scholak et al 2021 - PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models]]
     * [[https://arxiv.org/pdf/2201.11227.pdf|Poesia et al 2022 - Synchromesh: Reliable Code Generation from Pre-trained Language Models]] They created a tool that will take a ANTLR parser and a string, and give you the set of valid next token completions (see sect 3.1).     * [[https://arxiv.org/pdf/2201.11227.pdf|Poesia et al 2022 - Synchromesh: Reliable Code Generation from Pre-trained Language Models]] They created a tool that will take a ANTLR parser and a string, and give you the set of valid next token completions (see sect 3.1).
 +    * **[[https://arxiv.org/pdf/2305.13971|Geng et al 2023 - Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning]]** Elegant solution. Uses Grammatical Framework to constrain the outputs.
     * **[[https://arxiv.org/pdf/2403.06988|Beurer-Kellner et al 2024 - Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation]]**     * **[[https://arxiv.org/pdf/2403.06988|Beurer-Kellner et al 2024 - Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation]]**
   * **Parallel Decoding**   * **Parallel Decoding**
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   * **Speculative Decoding**   * **Speculative Decoding**
     * Overviews     * Overviews
 +      * [[https://arxiv.org/pdf/2401.07851|Xia et al 2024 - Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding]]
       * [[https://arxiv.org/pdf/2405.13019|Khoshnoodi et al 2024 - A Comprehensive Survey of Accelerated Generation Techniques in Large Language Models]]       * [[https://arxiv.org/pdf/2405.13019|Khoshnoodi et al 2024 - A Comprehensive Survey of Accelerated Generation Techniques in Large Language Models]]
     * [[https://arxiv.org/pdf/2211.17192|Leviathan et al 2024 - Fast Inference from Transformers via Speculative Decoding]]     * [[https://arxiv.org/pdf/2211.17192|Leviathan et al 2024 - Fast Inference from Transformers via Speculative Decoding]]
     * [[https://arxiv.org/pdf/2404.11912|Sun et al 2024 - TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding]]     * [[https://arxiv.org/pdf/2404.11912|Sun et al 2024 - TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding]]
 +    * [[https://arxiv.org/pdf/2502.17421|Yang et al 2025 - LongSpec: Long-Context Speculative Decoding with Efficient Drafting and Verification]]
 +    * [[https://arxiv.org/pdf/2505.20776|Cha et al 2025 - SpecExtend: A Drop-in Enhancement for Speculative Decoding of Long Sequences]]
   * **Miscellaneous Decoding Techniques**   * **Miscellaneous Decoding Techniques**
     * Contrastive Decoding     * Contrastive Decoding
nlp/seq2seq.1731876389.txt.gz · Last modified: 2024/11/17 20:46 by jmflanig
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