“‘NN Sampling’ Tag”,2019-10-29 (; backlinks):
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Bibliography for tag
ai/nn/sampling, most recent first: 2 related tags, 118 annotations, & 17 links (parent).
- See Also
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- Links
- “Do LLMs Estimate Uncertainty Well in Instruction-Following?”, et al 2024
- “SimpleStrat: Diversifying Language Model Generation With Stratification”, et al 2024
- “Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs”, et al 2024
- “Be like a Goldfish, Don’t Memorize! Mitigating Memorization in Generative LLMs”, et al 2024
- “Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass”, et al 2024
- “Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo”, et al 2024
- “Σ-GPTs: A New Approach to Autoregressive Models”, et al 2024
- “LLM Evaluators Recognize and Favor Their Own Generations”, et al 2024
- “Re-Evaluating GPT-4’s Bar Exam Performance”, 2024
- “Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking”, et al 2024
- “Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews”, et al 2024
- “Chain-Of-Thought Reasoning Without Prompting”, 2024
- “The Non-Effect of Sampling Temperature on Problem Solving in GPT-3.5/GPT-4”, 2024
- “Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM”, et al 2024
- “GIVT: Generative Infinite-Vocabulary Transformers”, et al 2023
- “Universal Self-Consistency for Large Language Model Generation”, et al 2023
- “Controlled Text Generation via Language Model Arithmetic”, et al 2023
- “Language Model Inversion”, et al 2023
- “SEDD: Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution”, et al 2023
- “Let Models Speak Ciphers: Multiagent Debate through Embeddings”, et al 2023
- “Contrastive Decoding Improves Reasoning in Large Language Models”, 2023
- “Accelerating LLM Inference With Staged Speculative Decoding”, 2023
- “Efficient Guided Generation for Large Language Models”, 2023
- “Copy Is All You Need”, et al 2023
- “Stay on Topic With Classifier-Free Guidance”, et al 2023
- “Sequential Monte Carlo Steering of Large Language Models Using Probabilistic Programs”, et al 2023
- “How Language Model Hallucinations Can Snowball”, et al 2023
- “Tractable Control for Autoregressive Language Generation”, et al 2023
- “MUX-PLMs: Pre-Training Language Models With Data Multiplexing”, et al 2023
- “Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, et al 2023
- “DataMUX: Data Multiplexing for Neural Networks”, et al 2023
- “Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation”, 2023
- “A Survey on Text Generation Using Generative Adversarial Networks”, 2022
- “Fast Inference from Transformers via Speculative Decoding”, et al 2022
- “The CRINGE Loss: Learning What Language Not to Model”, et al 2022
- “Contrastive Decoding: Open-Ended Text Generation As Optimization”, et al 2022
- “Help Me Write a Poem: Instruction Tuning As a Vehicle for Collaborative Poetry Writing (CoPoet)”, et al 2022
- “Contrastive Search Is What You Need For Neural Text Generation”, 2022
- “Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models”, et al 2022
- “Most Language Models Can Be Poets Too: An AI Writing Assistant and Constrained Text Generation Studio”, et al 2022
- “Ask Me Anything (AMA): A Simple Strategy for Prompting Language Models”, et al 2022
- “Out of One, Many: Using Language Models to Simulate Human Samples”, et al 2022
- “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”, et al 2022
- “Effidit: Your AI Writing Assistant”, et al 2022
- “DIRECTOR: Generator-Classifiers For Supervised Language Modeling”, et al 2022
- “RankGen: Improving Text Generation With Large Ranking Models”, et al 2022
- “Time Control: Language Modeling via Stochastic Processes”, et al 2022
- “Controllable Natural Language Generation With Contrastive Prefixes”, et al 2022
- “Using Natural Language Prompts for Machine Translation”, 2022
- “A Contrastive Framework for Neural Text Generation”, et al 2022
- “Typical Decoding for Natural Language Generation”, et al 2022
- “FIGARO: Generating Symbolic Music With Fine-Grained Artistic Control”, et al 2022
- “A Survey of Controllable Text Generation Using Transformer-Based Pre-Trained Language Models”, et al 2022
- “FRUIT: Faithfully Reflecting Updated Information in Text”, IV et al 2021
- “NeuroLogic A✱esque Decoding: Constrained Text Generation With Lookahead Heuristics”, et al 2021
- “Relating Neural Text Degeneration to Exposure Bias”, 2021
- “Program Synthesis With Large Language Models”, et al 2021
- “Scarecrow: A Framework for Scrutinizing Machine Text”, et al 2021
- “Time-Aware Language Models As Temporal Knowledge Bases”, et al 2021
- “Machine Translation Decoding beyond Beam Search”, et al 2021
- “Controllable Generation from Pre-Trained Language Models via Inverse Prompting”, et al 2021
- “Improving Diversity of Neural Text Generation via Inverse Probability Weighting”, et al 2021
- “There Once Was a Really Bad Poet, It Was Automated but You Didn’t Know It”, et al 2021
- “A✱ Search Without Expansions: Learning Heuristic Functions With Deep Q-Networks”, et al 2021
- “MAUVE: Measuring the Gap Between Neural Text and Human Text Using Divergence Frontiers”, et al 2021
- “Prefix-Tuning: Optimizing Continuous Prompts for Generation”, 2021
- “Bot-Adversarial Dialogue for Safe Conversational Agents”, et al 2021
- “Collaborative Storytelling With Large-Scale Neural Language Models”, et al 2020
- “NeuroLogic Decoding: (Un)supervised Neural Text Generation With Predicate Logic Constraints”, et al 2020
- “Interacting With GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation”, Geerlings & Meroño-2020
- “Training Independent Subnetworks for Robust Prediction”, et al 2020
- “MEGATRON-CNTRL: Controllable Story Generation With External Knowledge Using Large-Scale Language Models”, et al 2020
- “Weird AI Yankovic: Generating Parody Lyrics”, 2020
- “A Systematic Characterization of Sampling Algorithms for Open-Ended Language Generation”, et al 2020
- “GeDi: Generative Discriminator Guided Sequence Generation”, et al 2020
- “Mirostat: A Neural Text Decoding Algorithm That Directly Controls Perplexity”, et al 2020
- “Progressive Generation of Long Text”, et al 2020
- “This Word Does Not Exist”, 2020
- “True_poetry: Poetry Generator by GPT-2 With Meter and Rhyme Constraints”, Summers-2020
- “Blender: A State-Of-The-Art Open Source Chatbot”, et al 2020
- “Trading Off Diversity and Quality in Natural Language Generation”, et al 2020
- “Rapformer: Conditional Rap Lyrics Generation With Denoising Autoencoders”, et al 2020
- “A Hundred Visions and Revisions”, 2020
- “Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples”, et al 2020
- “Towards a Human-Like Open-Domain Chatbot”, et al 2020
- “Controlling Text Generation With Plug and Play Language Models”, et al 2019
- “Plug and Play Language Models: A Simple Approach to Controlled Text Generation”, et al 2019
- “CTRL: A Conditional Transformer Language Model For Controllable Generation”, et al 2019
- “Neural Text Generation With Unlikelihood Training”, et al 2019
- “GROVER: Defending Against Neural Fake News”, et al 2019
- “The Curious Case of Neural Text Degeneration”, et al 2019
- “Good News, Everyone! Context Driven Entity-Aware Captioning for News Images”, et al 2019
- “GPT-2 Neural Network Poetry”, 2019
- “Insertion Transformer: Flexible Sequence Generation via Insertion Operations”, et al 2019
- “Blockwise Parallel Decoding for Deep Autoregressive Models”, et al 2018
- “Language GANs Falling Short”, et al 2018
- “Discriminator Rejection Sampling”, et al 2018
- “OCD: Optimal Completion Distillation for Sequence Learning”, et al 2018
- “Controlling Linguistic Style Aspects in Neural Language Generation”, 2017
- “Six Challenges for Neural Machine Translation”, 2017
- “Language Generation With Recurrent Generative Adversarial Networks without Pre-Training”, et al 2017
- “A Deep Reinforced Model for Abstractive Summarization”, et al 2017
- “Learning to Generate Reviews and Discovering Sentiment”, et al 2017
- “Improving Neural Machine Translation With Conditional Sequence Generative Adversarial Nets”, et al 2017
- “Tuning Recurrent Neural Networks With Reinforcement Learning”, et al 2017
- “Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation”, et al 2016
- “WaveNet: A Generative Model for Raw Audio”, et al 2016
- “Sequence Level Training With Recurrent Neural Networks”, et al 2015
- “Generative Concatenative Nets Jointly Learn to Write and Classify Reviews”, et al 2015
- “Semi-Supervised Sequence Learning”, 2015
- “Scheduled Sampling for Sequence Prediction With Recurrent Neural Networks”, et al 2015
- “Controlling GPT-3 With Logit Bias”
- “Feature: Beam Search for Improving Global Quality of New Text Samples”
- “Exclude Top Choices (XTC): A Sampler That Boosts Creativity, Breaks Writing Clichés, and Inhibits Non-Verbatim Repetition”
- “Prompting Diverse Ideas: Increasing AI Idea Variance”
- “Pixels Still Beat Text: Attacking the OpenAI CLIP Model With Text Patches and Adversarial Pixel Perturbations”
- “Me, Myself, and AI: the Situational Awareness Dataset (SAD) for LLMs”
- “Apple or IPod? Easy Fix for Adversarial Textual Attacks on OpenAI’s CLIP Model!”
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