NN sequence sampling tag

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See Also

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Links

“Tractable Control for Autoregressive Language Generation”, Zhang Et Al 2023

“Tractable Control for Autoregressive Language Generation”

“Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, Aksitov Et Al 2023

“Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”

“Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation”, Toplyn2023

“Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation”

“Fast Inference from Transformers via Speculative Decoding”, Leviathan Et Al 2022

“Fast Inference from Transformers via Speculative Decoding”

“The CRINGE Loss: Learning What Language Not to Model”, Adolphs Et Al 2022

“The CRINGE Loss: Learning what language not to model”

“Contrastive Search Is What You Need For Neural Text Generation”, Su & Collier2022

“Contrastive Search Is What You Need For Neural Text Generation”

“Help Me Write a Poem: Instruction Tuning As a Vehicle for Collaborative Poetry Writing (CoPoet)”, Chakrabarty Et Al 2022

“Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing (CoPoet)”

“Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models”, Vilnis Et Al 2022

“Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models”

“Most Language Models Can Be Poets Too: An AI Writing Assistant and Constrained Text Generation Studio”, Roush Et Al 2022

“Most Language Models can be Poets too: An AI Writing Assistant and Constrained Text Generation Studio”

“Ask Me Anything (AMA): A Simple Strategy for Prompting Language Models”, Arora Et Al 2022

“Ask Me Anything (AMA): A simple strategy for prompting language models”

“Out of One, Many: Using Language Models to Simulate Human Samples”, Argyle Et Al 2022

“Out of One, Many: Using Language Models to Simulate Human Samples”

“Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”, Ganguli Et Al 2022

“Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”

“Effidit: Your AI Writing Assistant”, Shi Et Al 2022

“Effidit: Your AI Writing Assistant”

“DIRECTOR: Generator-Classifiers For Supervised Language Modeling”, Arora Et Al 2022

“DIRECTOR: Generator-Classifiers For Supervised Language Modeling”

“RankGen: Improving Text Generation With Large Ranking Models”, Krishna Et Al 2022

“RankGen: Improving Text Generation with Large Ranking Models”

“Controllable Natural Language Generation With Contrastive Prefixes”, Qian Et Al 2022

“Controllable Natural Language Generation with Contrastive Prefixes”

“Using Natural Language Prompts for Machine Translation”, Garcia & Firat2022

“Using natural language prompts for machine translation”

“A Contrastive Framework for Neural Text Generation”, Su Et Al 2022

“A Contrastive Framework for Neural Text Generation”

“Typical Decoding for Natural Language Generation”, Meister Et Al 2022

“Typical Decoding for Natural Language Generation”

“FIGARO: Generating Symbolic Music With Fine-Grained Artistic Control”, Rütte Et Al 2022

“FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control”

“A Survey of Controllable Text Generation Using Transformer-based Pre-trained Language Models”, Zhang Et Al 2022

“A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models”

“NeuroLogic A^*Esque Decoding: Constrained Text Generation With Lookahead Heuristics”, Lu Et Al 2021

“NeuroLogic A^*esque Decoding: Constrained Text Generation with Lookahead Heuristics”

“Program Synthesis With Large Language Models”, Austin Et Al 2021

“Program Synthesis with Large Language Models”

“Scarecrow: A Framework for Scrutinizing Machine Text”, Dou Et Al 2021

“Scarecrow: A Framework for Scrutinizing Machine Text”

“Time-Aware Language Models As Temporal Knowledge Bases”, Dhingra Et Al 2021

“Time-Aware Language Models as Temporal Knowledge Bases”

“Choose-Your-Own-Adventure AI Dungeon Games”, Gwern 2021

“Choose-Your-Own-Adventure AI Dungeon Games”

“Machine Translation Decoding beyond Beam Search”, Leblond Et Al 2021

“Machine Translation Decoding beyond Beam Search”

“Controllable Generation from Pre-trained Language Models via Inverse Prompting”, Zou Et Al 2021

“Controllable Generation from Pre-trained Language Models via Inverse Prompting”

“Improving Diversity of Neural Text Generation via Inverse Probability Weighting”, Zhang Et Al 2021

“Improving Diversity of Neural Text Generation via Inverse Probability Weighting”

“There Once Was a Really Bad Poet, It Was Automated but You Didn’t Know It”, Wang Et Al 2021

“There Once Was a Really Bad Poet, It Was Automated but You Didn’t Know It”

“MAUVE: Measuring the Gap Between Neural Text and Human Text Using Divergence Frontiers”, Pillutla Et Al 2021

“MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers”

“Prefix-Tuning: Optimizing Continuous Prompts for Generation”, Li & Liang2021

“Prefix-Tuning: Optimizing Continuous Prompts for Generation”

“Bot-Adversarial Dialogue for Safe Conversational Agents”, Xu Et Al 2021

“Bot-Adversarial Dialogue for Safe Conversational Agents”

“Collaborative Storytelling With Large-scale Neural Language Models”, Nichols Et Al 2020

“Collaborative Storytelling with Large-scale Neural Language Models”

“NeuroLogic Decoding: (Un)supervised Neural Text Generation With Predicate Logic Constraints”, Lu Et Al 2020

“NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints”

“Interacting With GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”, Geerlings & Meroño-Peñuela2020

“Interacting with GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”

“MEGATRON-CNTRL: Controllable Story Generation With External Knowledge Using Large-Scale Language Models”, Xu Et Al 2020

“MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models”

“Weird AI Yankovic: Generating Parody Lyrics”, Riedl2020

“Weird AI Yankovic: Generating Parody Lyrics”

“A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation”, Nadeem Et Al 2020

“A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation”

“GeDi: Generative Discriminator Guided Sequence Generation”, Krause Et Al 2020

“GeDi: Generative Discriminator Guided Sequence Generation”

“Mirostat: A Neural Text Decoding Algorithm That Directly Controls Perplexity”, Basu Et Al 2020

“Mirostat: A Neural Text Decoding Algorithm that Directly Controls Perplexity”

“Progressive Generation of Long Text”, Tan Et Al 2020

“Progressive Generation of Long Text”

“GPT-3 Creative Fiction”, Gwern 2020

“GPT-3 Creative Fiction”

“This Word Does Not Exist”, Dimson2020

“This Word Does Not Exist”

“True_poetry: Poetry Generator by GPT-2 With Meter and Rhyme Constraints”, Summers-Stay2020

“true_poetry: Poetry generator by GPT-2 with meter and rhyme constraints”

“Blender: A State-of-the-art Open Source Chatbot”, Roller Et Al 2020

“Blender: A state-of-the-art open source chatbot”

“Trading Off Diversity and Quality in Natural Language Generation”, Zhang Et Al 2020

“Trading Off Diversity and Quality in Natural Language Generation”

“Rapformer: Conditional Rap Lyrics Generation With Denoising Autoencoders”, Nikolov Et Al 2020

“Rapformer: Conditional Rap Lyrics Generation with Denoising Autoencoders”

“A Hundred Visions and Revisions”, Binder2020

“A Hundred Visions and Revisions”

“Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples”, Sinha Et Al 2020

“Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples”

“Towards a Human-like Open-Domain Chatbot”, Adiwardana Et Al 2020

“Towards a Human-like Open-Domain Chatbot”

“Controlling Text Generation With Plug and Play Language Models”, Liu Et Al 2019

“Controlling Text Generation with Plug and Play Language Models”

“Plug and Play Language Models: A Simple Approach to Controlled Text Generation”, Dathathri Et Al 2019

“Plug and Play Language Models: A Simple Approach to Controlled Text Generation”

“CTRL: A Conditional Transformer Language Model For Controllable Generation”, Keskar Et Al 2019

“CTRL: A Conditional Transformer Language Model For Controllable Generation”

“Neural Text Generation With Unlikelihood Training”, Welleck Et Al 2019

“Neural Text Generation with Unlikelihood Training”

“GROVER: Defending Against Neural Fake News”, Zellers Et Al 2019

“GROVER: Defending Against Neural Fake News”

“The Curious Case of Neural Text Degeneration”, Holtzman Et Al 2019

“The Curious Case of Neural Text Degeneration”

“Good News, Everyone! Context Driven Entity-aware Captioning for News Images”, Biten Et Al 2019

“Good News, Everyone! Context driven entity-aware captioning for news images”

“GPT-2 Neural Network Poetry”, Gwern & Presser2019

“GPT-2 Neural Network Poetry”

“Controlling Linguistic Style Aspects in Neural Language Generation”, Ficler & Goldberg2017

“Controlling Linguistic Style Aspects in Neural Language Generation”

“Language Generation With Recurrent Generative Adversarial Networks without Pre-training”, Press Et Al 2017

“Language Generation with Recurrent Generative Adversarial Networks without Pre-training”

“A Deep Reinforced Model for Abstractive Summarization”, Paulus Et Al 2017

“A Deep Reinforced Model for Abstractive Summarization”

“Learning to Generate Reviews and Discovering Sentiment”, Radford Et Al 2017

“Learning to Generate Reviews and Discovering Sentiment”

“Improving Neural Machine Translation With Conditional Sequence Generative Adversarial Nets”, Yang Et Al 2017

“Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets”

“Tuning Recurrent Neural Networks With Reinforcement Learning”, Jaques Et Al 2017

“Tuning Recurrent Neural Networks with Reinforcement Learning”

“Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation”, Johnson Et Al 2016

“Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation”

“WaveNet: A Generative Model for Raw Audio”, Oord Et Al 2016

“WaveNet: A Generative Model for Raw Audio”

“Sequence Level Training With Recurrent Neural Networks”, Ranzato Et Al 2015

“Sequence Level Training with Recurrent Neural Networks”

“Generative Concatenative Nets Jointly Learn to Write and Classify Reviews”, Lipton Et Al 2015

“Generative Concatenative Nets Jointly Learn to Write and Classify Reviews”

“Semi-supervised Sequence Learning”, Dai & Le2015

“Semi-supervised Sequence Learning”

“RNN Metadata for Mimicking Author Style”, Gwern 2015

“RNN Metadata for Mimicking Author Style”

“Scheduled Sampling for Sequence Prediction With Recurrent Neural Networks”, Bengio Et Al 2015

“Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks”

“Pixels Still Beat Text: Attacking the OpenAI CLIP Model With Text Patches and Adversarial Pixel Perturbations”

“Pixels still beat text: Attacking the OpenAI CLIP model with text patches and adversarial pixel perturbations”

“Apple or IPod? Easy Fix for Adversarial Textual Attacks on OpenAI’s CLIP Model!”

“Apple or iPod? Easy Fix for Adversarial Textual Attacks on OpenAI's CLIP Model!”

Wikipedia

Miscellaneous

Link Bibliography

https://arxiv.org/abs/2210.14140: “Contrastive Search Is What You Need For Neural Text Generation”⁠, Yixuan Su, Nigel Collier

link-bibliography
https://arxiv.org/abs/2210.13669: “Help Me Write a Poem: Instruction Tuning As a Vehicle for Collaborative Poetry Writing (CoPoet)”⁠, Tuhin Chakrabarty, Vishakh Padmakumar, He He

link-bibliography
https://arxiv.org/abs/2210.15458#google: “Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models”⁠, Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Passos, Sumit Sanghai

link-bibliography
https://aclanthology.org/2022.cai-1.2.pdf: “Most Language Models Can Be Poets Too: An AI Writing Assistant and Constrained Text Generation Studio”⁠, Allen Roush, Sanjay Basu, Akshay Moorthy, Dmitry Dubovoy

link-bibliography
https://arxiv.org/abs/2210.02441: “Ask Me Anything (AMA): A Simple Strategy for Prompting Language Models”⁠, Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala

link-bibliography
https://www.anthropic.com/red_teaming.pdf: “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”⁠, Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez

link-bibliography
https://arxiv.org/abs/2202.11822#google: “Using Natural Language Prompts for Machine Translation”⁠, Xavier Garcia, Orhan Firat

link-bibliography
https://arxiv.org/abs/2107.01294#allen: “Scarecrow: A Framework for Scrutinizing Machine Text”⁠, Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A. Smith, Yejin Choi

link-bibliography
cyoa: “Choose-Your-Own-Adventure AI Dungeon Games”⁠, gwern

link-bibliography
https://arxiv.org/abs/2101.00190: “Prefix-Tuning: Optimizing Continuous Prompts for Generation”⁠, Xiang Lisa Li, Percy Liang

link-bibliography
https://aclanthology.org/2021.naacl-main.235.pdf#facebook: “Bot-Adversarial Dialogue for Safe Conversational Agents”⁠, Jing Xu, Da Ju, Margaret Li, Y-Lan Boureau, Jason Weston, Emily Dinan

link-bibliography
gpt-3: “GPT-3 Creative Fiction”⁠, gwern

link-bibliography
https://www.thisworddoesnotexist.com/: “This Word Does Not Exist”⁠, Thomas Dimson

link-bibliography
https://ai.facebook.com/blog/state-of-the-art-open-source-chatbot: “Blender: A State-of-the-art Open Source Chatbot”⁠, Stephen Roller, Jason Weston, Emily Dinan

link-bibliography
https://arxiv.org/abs/2004.03965: “Rapformer: Conditional Rap Lyrics Generation With Denoising Autoencoders”⁠, Nikola I. Nikolov, Eric Malmi, Curtis G. Northcutt, Loreto Parisi

link-bibliography
https://www.uber.com/blog/pplm/: “Controlling Text Generation With Plug and Play Language Models”⁠, Rosanne Liu, Sumanth Dathathri, Andrea Madotto, Piero Molino, Jason Yosinski

link-bibliography
https://arxiv.org/abs/1909.05858#salesforce: “CTRL: A Conditional Transformer Language Model For Controllable Generation”⁠, Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, Caiming Xiong, Richard Socher (Salesforce)

link-bibliography
gpt-2: “GPT-2 Neural Network Poetry”⁠, gwern, Shawn Presser

link-bibliography
rnn-metadata: “RNN Metadata for Mimicking Author Style”⁠, gwern

link-bibliography

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