- See Also
-
Links
- “Contrastive Decoding Improves Reasoning in Large Language Models”, O’Brien & Lewis 2023
- “Accelerating LLM Inference With Staged Speculative Decoding”, Spector & Re 2023
- “Copy Is All You Need”, Lan et al 2023
- “Stay on Topic With Classifier-Free Guidance”, Sanchez et al 2023
- “Sequential Monte Carlo Steering of Large Language Models Using Probabilistic Programs”, Lew et al 2023
- “How Language Model Hallucinations Can Snowball”, Zhang et al 2023
- “Tractable Control for Autoregressive Language Generation”, Zhang et al 2023
- “Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, Aksitov et al 2023
- “Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation”, Toplyn 2023
- “Fast Inference from Transformers via Speculative Decoding”, Leviathan et al 2022
- “The CRINGE Loss: Learning What Language Not to Model”, Adolphs et al 2022
- “Contrastive Decoding: Open-ended Text Generation As Optimization”, Li et al 2022
- “Contrastive Search Is What You Need For Neural Text Generation”, Su & Collier 2022
- “Help Me Write a Poem: Instruction Tuning As a Vehicle for Collaborative Poetry Writing (CoPoet)”, Chakrabarty et al 2022
- “Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models”, Vilnis et al 2022
- “Most Language Models Can Be Poets Too: An AI Writing Assistant and Constrained Text Generation Studio”, Roush et al 2022
- “Ask Me Anything (AMA): A Simple Strategy for Prompting Language Models”, Arora et al 2022
- “Out of One, Many: Using Language Models to Simulate Human Samples”, Argyle et al 2022
- “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”, Ganguli et al 2022
- “Effidit: Your AI Writing Assistant”, Shi et al 2022
- “DIRECTOR: Generator-Classifiers For Supervised Language Modeling”, Arora et al 2022
- “RankGen: Improving Text Generation With Large Ranking Models”, Krishna et al 2022
- “Controllable Natural Language Generation With Contrastive Prefixes”, Qian et al 2022
- “Using Natural Language Prompts for Machine Translation”, Garcia & Firat 2022
- “A Contrastive Framework for Neural Text Generation”, Su et al 2022
- “Typical Decoding for Natural Language Generation”, Meister et al 2022
- “FIGARO: Generating Symbolic Music With Fine-Grained Artistic Control”, Rütte et al 2022
- “A Survey of Controllable Text Generation Using Transformer-based Pre-trained Language Models”, Zhang et al 2022
- “NeuroLogic A✱esque Decoding: Constrained Text Generation With Lookahead Heuristics”, Lu et al 2021
- “Relating Neural Text Degeneration to Exposure Bias”, Chiang & Chen 2021
- “Program Synthesis With Large Language Models”, Austin et al 2021
- “Scarecrow: A Framework for Scrutinizing Machine Text”, Dou et al 2021
- “Time-Aware Language Models As Temporal Knowledge Bases”, Dhingra et al 2021
- “Choose-Your-Own-Adventure AI Dungeon Games”, Gwern 2021
- “Machine Translation Decoding beyond Beam Search”, Leblond et al 2021
- “Controllable Generation from Pre-trained Language Models via Inverse Prompting”, Zou et al 2021
- “Improving Diversity of Neural Text Generation via Inverse Probability Weighting”, Zhang et al 2021
- “There Once Was a Really Bad Poet, It Was Automated but You Didn’t Know It”, Wang et al 2021
- “MAUVE: Measuring the Gap Between Neural Text and Human Text Using Divergence Frontiers”, Pillutla et al 2021
- “Prefix-Tuning: Optimizing Continuous Prompts for Generation”, Li & Liang 2021
- “Bot-Adversarial Dialogue for Safe Conversational Agents”, Xu et al 2021
- “Collaborative Storytelling With Large-scale Neural Language Models”, Nichols et al 2020
- “NeuroLogic Decoding: (Un)supervised Neural Text Generation With Predicate Logic Constraints”, Lu et al 2020
- “Interacting With GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”, Geerlings & Meroño-Peñuela 2020
- “MEGATRON-CNTRL: Controllable Story Generation With External Knowledge Using Large-Scale Language Models”, Xu et al 2020
- “Weird AI Yankovic: Generating Parody Lyrics”, Riedl 2020
- “A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation”, Nadeem et al 2020
- “GeDi: Generative Discriminator Guided Sequence Generation”, Krause et al 2020
- “Mirostat: A Neural Text Decoding Algorithm That Directly Controls Perplexity”, Basu et al 2020
- “Progressive Generation of Long Text”, Tan et al 2020
- “GPT-3 Creative Fiction”, Gwern 2020
- “This Word Does Not Exist”, Dimson 2020
- “True_poetry: Poetry Generator by GPT-2 With Meter and Rhyme Constraints”, Summers-Stay 2020
- “Blender: A State-of-the-art Open Source Chatbot”, Roller et al 2020
- “Trading Off Diversity and Quality in Natural Language Generation”, Zhang et al 2020
- “Rapformer: Conditional Rap Lyrics Generation With Denoising Autoencoders”, Nikolov et al 2020
- “A Hundred Visions and Revisions”, Binder 2020
- “Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples”, Sinha et al 2020
- “Towards a Human-like Open-Domain Chatbot”, Adiwardana et al 2020
- “Controlling Text Generation With Plug and Play Language Models”, Liu et al 2019
- “Plug and Play Language Models: A Simple Approach to Controlled Text Generation”, Dathathri et al 2019
- “CTRL: A Conditional Transformer Language Model For Controllable Generation”, Keskar et al 2019
- “Neural Text Generation With Unlikelihood Training”, Welleck et al 2019
- “GROVER: Defending Against Neural Fake News”, Zellers et al 2019
- “The Curious Case of Neural Text Degeneration”, Holtzman et al 2019
- “Good News, Everyone! Context Driven Entity-aware Captioning for News Images”, Biten et al 2019
- “GPT-2 Neural Network Poetry”, Branwen & Presser 2019
- “Insertion Transformer: Flexible Sequence Generation via Insertion Operations”, Stern et al 2019
- “Blockwise Parallel Decoding for Deep Autoregressive Models”, Stern et al 2018
- “Controlling Linguistic Style Aspects in Neural Language Generation”, Ficler & Goldberg 2017
- “Language Generation With Recurrent Generative Adversarial Networks without Pre-training”, Press et al 2017
- “A Deep Reinforced Model for Abstractive Summarization”, Paulus et al 2017
- “Learning to Generate Reviews and Discovering Sentiment”, Radford et al 2017
- “Improving Neural Machine Translation With Conditional Sequence Generative Adversarial Nets”, Yang et al 2017
- “Tuning Recurrent Neural Networks With Reinforcement Learning”, Jaques et al 2017
- “Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation”, Johnson et al 2016
- “WaveNet: A Generative Model for Raw Audio”, Oord et al 2016
- “Sequence Level Training With Recurrent Neural Networks”, Ranzato et al 2015
- “Generative Concatenative Nets Jointly Learn to Write and Classify Reviews”, Lipton et al 2015
- “Semi-supervised Sequence Learning”, Dai & Le 2015
- “RNN Metadata for Mimicking Author Style”, Gwern 2015
- “Scheduled Sampling for Sequence Prediction With Recurrent Neural Networks”, Bengio et al 2015
- “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!”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Contrastive Decoding Improves Reasoning in Large Language Models”, O’Brien & Lewis 2023
“Contrastive Decoding Improves Reasoning in Large Language Models”
“Accelerating LLM Inference With Staged Speculative Decoding”, Spector & Re 2023
“Accelerating LLM Inference with Staged Speculative Decoding”
“Copy Is All You Need”, Lan et al 2023
“Stay on Topic With Classifier-Free Guidance”, Sanchez et al 2023
“Sequential Monte Carlo Steering of Large Language Models Using Probabilistic Programs”, Lew et al 2023
“Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs”
“How Language Model Hallucinations Can Snowball”, Zhang et al 2023
“Tractable Control for Autoregressive Language Generation”, Zhang et al 2023
“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”, Toplyn 2023
“Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation”
“Fast Inference from Transformers via Speculative Decoding”, Leviathan et al 2022
“The CRINGE Loss: Learning What Language Not to Model”, Adolphs et al 2022
“Contrastive Decoding: Open-ended Text Generation As Optimization”, Li et al 2022
“Contrastive Decoding: Open-ended Text Generation as Optimization”
“Contrastive Search Is What You Need For Neural Text Generation”, Su & Collier 2022
“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
“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
“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 & Firat 2022
“A Contrastive Framework for Neural Text Generation”, Su et al 2022
“Typical Decoding for Natural Language Generation”, Meister et al 2022
“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”
“Relating Neural Text Degeneration to Exposure Bias”, Chiang & Chen 2021
“Program Synthesis With Large Language Models”, Austin et al 2021
“Scarecrow: A Framework for Scrutinizing Machine Text”, Dou et al 2021
“Time-Aware Language Models As Temporal Knowledge Bases”, Dhingra et al 2021
“Choose-Your-Own-Adventure AI Dungeon Games”, Gwern 2021
“Machine Translation Decoding beyond Beam Search”, Leblond et al 2021
“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 & Liang 2021
“Prefix-Tuning: Optimizing Continuous Prompts for Generation”
“Bot-Adversarial Dialogue for Safe Conversational Agents”, Xu et al 2021
“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-Peñuela 2020
“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
“Weird AI Yankovic: Generating Parody Lyrics”, Riedl 2020
“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
“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
“GPT-3 Creative Fiction”, Gwern 2020
“This Word Does Not Exist”, Dimson 2020
“True_poetry: Poetry Generator by GPT-2 With Meter and Rhyme Constraints”, Summers-Stay 2020
“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
“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”, Binder 2020
“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
“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
“GROVER: Defending Against Neural Fake News”, Zellers et al 2019
“The Curious Case of Neural Text Degeneration”, Holtzman et al 2019
“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”, Branwen & Presser 2019
“Insertion Transformer: Flexible Sequence Generation via Insertion Operations”, Stern et al 2019
“Insertion Transformer: Flexible Sequence Generation via Insertion Operations”
“Blockwise Parallel Decoding for Deep Autoregressive Models”, Stern et al 2018
“Blockwise Parallel Decoding for Deep Autoregressive Models”
“Controlling Linguistic Style Aspects in Neural Language Generation”, Ficler & Goldberg 2017
“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
“Learning to Generate Reviews and Discovering Sentiment”, Radford et al 2017
“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
“Sequence Level Training With Recurrent Neural Networks”, Ranzato et al 2015
“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 & Le 2015
“RNN Metadata for Mimicking Author Style”, Gwern 2015
“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”
“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!”
Sort By Magic
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Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
language-models
controlled-text-generation
translation
poetry-generation
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Wikipedia
Miscellaneous
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https://homepages.inf.ed.ac.uk/abmayne/publications/sennrich2016NAACL.pdf -
https://mi.eng.cam.ac.uk/projects/cued-rnnlm/papers/Interspeech15.pdf -
https://workshop2015.iwslt.org/downloads/IWSLT_2015_RP_13.pdf
Link Bibliography
-
https://arxiv.org/abs/2309.09117#facebook: “Contrastive Decoding Improves Reasoning in Large Language Models”, Sean O’Brien, Mike Lewis -
https://arxiv.org/abs/2306.17806#eleutherai: “Stay on Topic With Classifier-Free Guidance”, Guillaume Sanchez, Honglu Fan, Alexander Spangher, Elad Levi, Pawan Sasanka Ammanamanchi, Stella Biderman -
https://arxiv.org/abs/2306.03081: “Sequential Monte Carlo Steering of Large Language Models Using Probabilistic Programs”, Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand, Vikash K. Mansinghka -
https://arxiv.org/abs/2305.13534: “How Language Model Hallucinations Can Snowball”, Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah A. Smith -
https://arxiv.org/abs/2210.15097: “Contrastive Decoding: Open-ended Text Generation As Optimization”, -
https://arxiv.org/abs/2210.14140: “Contrastive Search Is What You Need For Neural Text Generation”, Yixuan Su, Nigel Collier -
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 -
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 -
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 -
https://arxiv.org/abs/2210.02441: “Ask Me Anything (AMA): A Simple Strategy for Prompting Language Models”, -
https://www.anthropic.com/red_teaming.pdf: “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”, -
https://arxiv.org/abs/2202.11822#google: “Using Natural Language Prompts for Machine Translation”, Xavier Garcia, Orhan Firat -
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 -
cyoa: “Choose-Your-Own-Adventure AI Dungeon Games”, Gwern -
https://arxiv.org/abs/2101.00190: “Prefix-Tuning: Optimizing Continuous Prompts for Generation”, Xiang Lisa Li, Percy Liang -
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 -
gpt-3: “GPT-3 Creative Fiction”, Gwern -
https://www.thisworddoesnotexist.com/: “This Word Does Not Exist”, Thomas Dimson -
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 -
https://arxiv.org/abs/2004.03965: “Rapformer: Conditional Rap Lyrics Generation With Denoising Autoencoders”, Nikola I. Nikolov, Eric Malmi, Curtis G. Northcutt, Loreto Parisi -
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 -
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) -
gpt-2: “GPT-2 Neural Network Poetry”, Gwern Branwen, Shawn Presser -
https://arxiv.org/abs/1902.03249#google: “Insertion Transformer: Flexible Sequence Generation via Insertion Operations”, Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit -
rnn-metadata: “RNN Metadata for Mimicking Author Style”, Gwern