“‘GPT-3 Nonfiction’ Tag”,2020-10-06

Bibliography for tag ai/nn/transformer/gpt/3/nonfiction, most recent first: 125 annotations & 48 links (parent).

• See Also
• Links
  • “Can LLMs Be Scammed? A Baseline Measurement Study”, Sehwag et al 2024
  • “The Rise of AI-Generated Content in Wikipedia”, Brooks et al 2024
  • “On Scalable Oversight With Weak LLMs Judging Strong LLMs”, Kenton et al 2024
  • “APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets”, Liu et al 2024
  • “Connecting the Dots: LLMs Can Infer and Verbalize Latent Structure from Disparate Training Data”, Treutlein et al 2024
  • “Designing a Dashboard for Transparency and Control of Conversational AI”, Chen et al 2024
  • “Delving into ChatGPT Usage in Academic Writing through Excess Vocabulary”, Kobak et al 2024
  • “Do Teachers Spot AI? Evaluating the Detectability of AI-Generated Texts among Student Essays”, Fleckenstein et al 2024
  • “LLMs Achieve Adult Human Performance on Higher-Order Theory of Mind Tasks”, Street et al 2024
  • “Can Language Models Explain Their Own Classification Behavior?”, Sherburn et al 2024
  • “The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions”, Wallace et al 2024
  • “FABLES: Evaluating Faithfulness and Content Selection in Book-Length Summarization”, Kim et al 2024
  • “Vulnerability Detection With Code Language Models: How Far Are We?”, Ding et al 2024
  • “The NSA Warns That US Adversaries Free to Mine Private Data May Have an AI Edge: Gilbert Herrera, Who Leads Research at the National Security Agency, Says Large Language Models Are Incredibly Useful—And a Bit of a Headache—For America’s Intelligence Machine”, Knight2024
  • “Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews”, Liang et al 2024
  • “Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap”, Srivastava et al 2024
  • “Tokenization Counts: the Impact of Tokenization on Arithmetic in Frontier LLMs”, Singh & Strouse2024
  • “Who Is AI Replacing? The Impact of Generative AI on Online Freelancing Platforms”, Demirci et al 2024
  • “ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Jiang et al 2024
  • “Using Counterfactual Tasks to Evaluate the Generality of Analogical Reasoning in Large Language Models”, Lewis & Mitchell2024
  • “The Non-Effect of Sampling Temperature on Problem Solving in GPT-3.5/GPT-4”, Renze & Guven2024
  • “I Think, Therefore I Am: Benchmarking Awareness of Large Language Models Using AwareBench”, Li et al 2024
  • “Does Using ChatGPT Result in Human Cognitive Augmentation?”, Fulbright & Morrison2024
  • “A Vision Check-Up for Language Models”, Sharma et al 2024
  • “Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach”, Ma et al 2023
  • “TinyGSM: Achieving >80% on GSM8k With Small Language Models”, Liu et al 2023
  • “Universal Self-Consistency for Large Language Model Generation”, Chen et al 2023
  • “PEARL: Personalizing Large Language Model Writing Assistants With Generation-Calibrated Retrievers”, Mysore et al 2023
  • “Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations”, Hong et al 2023
  • “InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews”, Wang et al 2023
  • “Data Contamination Through the Lens of Time”, Roberts et al 2023
  • “Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams”, Callanan et al 2023
  • “Large Language Models Can Replicate Cross-Cultural Differences in Personality”, Niszczota et al 2023
  • “Beyond Memorization: Violating Privacy Via Inference With Large Language Models”, Staab et al 2023
  • “GeoLLM: Extracting Geospatial Knowledge from Large Language Models”, Manvi et al 2023
  • “Can a Computer Outfake a Human [Personality]?”, Phillips & Robie2023
  • “Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models”, Zhou et al 2023
  • “Using Large Language Models for Qualitative Analysis Can Introduce Serious Bias”, Ashwin et al 2023
  • “MTOB: A Benchmark for Learning to Translate a New Language from One Grammar Book”, Tanzer et al 2023
  • “Embers of Autoregression: Understanding Large Language Models Through the Problem They Are Trained to Solve”, McCoy et al 2023
  • “The Cambridge Law Corpus: A Corpus for Legal AI Research”, Östling et al 2023
  • “Assessing the Nature of Large Language Models: A Caution against Anthropocentrism”, Speed2023
  • “A Boy Saw 17 Doctors over 3 Years for Chronic Pain. ChatGPT Found the Diagnosis”, Holohan2023
  • “Taken out of Context: On Measuring Situational Awareness in LLMs”, Berglund et al 2023
  • “Investigating the Existence of ‘Secret Language’ in Language Models”, Wang et al 2023
  • “Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow”, Rio-Chanona et al 2023
  • “Machine-Assisted Social Psychology Hypothesis Generation”, Banker et al 2023
  • “Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events”, Gu et al 2023
  • “Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration”, Wang et al 2023
  • “Explaining Competitive-Level Programming Solutions Using LLMs”, Li et al 2023
  • “Lost in the Middle: How Language Models Use Long Contexts”, Liu et al 2023
  • “Hoodwinked: Deception and Cooperation in a Text-Based Game for Language Models”, O’Gara2023
  • “Language Models Are Weak Learners”, Manikandan et al 2023
  • “Understanding Social Reasoning in Language Models With Language Models”, Gandhi et al 2023
  • “Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
  • “Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks”, Veselovsky et al 2023
  • “Can Large Language Models Democratize Access to Dual-Use Biotechnology?”, Soice et al 2023
  • “Iterative Translation Refinement With Large Language Models”, Chen et al 2023
  • “Don’t Want Students to Rely on ChatGPT? Have Them Use It: It’s Easy to Forget How Little Students and Educators Understand Generative AI’s Flaws. Once They Actually Try It Out, They’ll See That It Can’t Replace Them”, Howell2023
  • “The Exciting Potential for ChatGPT in Obstetrics and Gynecology”, Grünebaum et al 2023
  • “Do GPTs Produce Less Literal Translations?”, Raunak et al 2023
  • “The False Promise of Imitating Proprietary LLMs”, Gudibande et al 2023
  • “Learning to Generate Novel Scientific Directions With Contextualized Literature-Based Discovery”, Wang et al 2023
  • “How Language Model Hallucinations Can Snowball”, Zhang et al 2023
  • “LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions”, Wu et al 2023
  • “Evaluating Transformer Language Models on Arithmetic Operations Using Number Decomposition”, Muffo et al 2023
  • “Generative AI at Work”, Brynjolfsson et al 2023
  • “Humans in Humans Out: On GPT Converging Toward Common Sense in Both Success and Failure”, Koralus & Wang-Maścianica2023
  • “Language Models Can Solve Computer Tasks”, Kim et al 2023
  • “Performance of ChatGPT on Free-Response, Clinical Reasoning Exams”, Strong et al 2023
  • “How Well Do Large Language Models Perform in Arithmetic Tasks?”, Yuan et al 2023
  • “Larger Language Models Do In-Context Learning Differently”, Wei et al 2023
  • “Is ChatGPT a General-Purpose Natural Language Processing Task Solver?”, Qin et al 2023
  • “Predicting Consumer Contracts [With GPT-3]”, Kolt2023
  • “Use GPT-3 Incorrectly: Reduce Costs 40× and Increase Speed by 5×”, Pullen2023
  • “A Judge Just Used ChatGPT to Make a Court Decision: The Case Is the First Time a Court Has Admitted to Using the AI Text Generator’s Answers in a Legal Ruling”, Rose2023
  • “Co-Writing With Opinionated Language Models Affects Users’ Views”, Jakesch et al 2023
  • “The inside Story of ChatGPT: How OpenAI Founder Sam Altman Built the World’s Hottest Technology With Billions from Microsoft”, Kahn2023
  • “How Close Is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection”, Guo et al 2023
  • “Can GPT-3 Produce New Ideas? Partially Automating Robin Hanson and Others § If You Never Miss a Plane…”, Sempere2023
  • “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment”, Gilson et al 2023
  • “GPT-3 Takes the Bar Exam”, II & Katz2022
  • “Precise Zero-Shot Dense Retrieval without Relevance Labels”, Gao et al 2022
  • “Self-Instruct: Aligning Language Models With Self-Generated Instructions”, Wang et al 2022
  • “Emergent Analogical Reasoning in Large Language Models”, Webb et al 2022
  • “Harvey, Which Uses AI to Answer Legal Questions, Lands Cash from OpenAI”, Wiggers2022
  • “LMentry: A Language Model Benchmark of Elementary Language Tasks”, Efrat et al 2022
  • “Self-Ask: Measuring and Narrowing the Compositionality Gap in Language Models (Bamboogle)”, Press et al 2022
  • “How Persuasive Is AI-Generated Argumentation? An Analysis of the Quality of an Argumentative Text Produced by the GPT-3 AI Text Generator”, Hinton & Wagemans2022
  • “Out of One, Many: Using Language Models to Simulate Human Samples”, Argyle et al 2022
  • “What Does a Platypus Look Like? Generating Customized Prompts for Zero-Shot Image Classification (CuPL)”, Pratt et al 2022
  • “Using Large Language Models to Simulate Multiple Humans”, Aher et al 2022
  • “Limitations of Language Models in Arithmetic and Symbolic Induction”, Qian et al 2022
  • “RealTime QA: What’s the Answer Right Now?”, Kasai et al 2022
  • “GODEL: Large-Scale Pre-Training for Goal-Directed Dialog”, Peng et al 2022
  • “Can GPT-3 Write an Academic Paper on Itself, With Minimal Human Input?”, GPT-3 et al 2022 (page 2)
  • “NaturalProver: Grounded Mathematical Proof Generation With Language Models”, Welleck et al 2022
  • “OPT: Open Pre-Trained Transformer Language Models”, Zhang et al 2022
  • “InstructGPT: Training Language Models to Follow Instructions With Human Feedback”, Ouyang et al 2022
  • “Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?”, Min et al 2022
  • “Impact of Pretraining Term Frequencies on Few-Shot Reasoning”, Razeghi et al 2022
  • “Contracts in the Age of Smart Readers”, Arbel & Becher2022
  • “Memory-Assisted Prompt Editing to Improve GPT-3 After Deployment”, Madaan et al 2022
  • “CommonsenseQA 2.0: Exposing the Limits of AI through Gamification”, Talmor et al 2022
  • “Limits of Using Artificial Intelligence and GPT-3 in Patent Prosecution”, Tu et al 2022
  • “What Can a Generative Language Model Answer About a Passage?”, Summers-Stay et al 2021
  • “Process for Adapting Language Models to Society (PALMS) With Values-Targeted Datasets”, Solaiman & Dennison2021
  • “Scaling Laws for Autoregressive Generative Modeling”, Henighan et al 2020
  • “GPT-3: Its Nature, Scope, Limits, and Consequences”, Floridi & Chiriatti2020
  • “MMLU: Measuring Massive Multitask Language Understanding”, Hendrycks et al 2020
  • “GPT-3: Language Models Are Few-Shot Learners”, Brown et al 2020
  • “Extrapolating to Unnatural Language Processing With GPT-3’s In-Context Learning: The Good, the Bad, and the Mysterious”
  • “Janus”
  • “Fine-Tuning Is Not Sufficient for Capability Elicitation”
  • “Connecting the Dots: LLMs Can Infer & Verbalize Latent Structure from Training Data”
  • “Reward Hacking Behavior Can Generalize across Tasks”
  • “Who Models the Models That Model Models? An Exploration of GPT-3’s In-Context Model Fitting Ability”
  • “GPT-3 Catching Fish in Morse Code”
  • “A Robot Wrote This Entire Article. Are You Scared Yet, Human? We Asked GPT-3, OpenAI’s Powerful New Language Generator, to Write an Essay for Us from Scratch. The Assignment? To Convince Us Robots Come in Peace | For More about GPT-3 and How This Essay Was Written and Edited, Please Read Our Editor’s Note Below”
  • MelMitchell1
  • SRajdev
  • bucketofkets
  • hamandcheese
  • sakun135
  • spolu
  • Sort By Magic
    • legal-ai
    • literature-discovery
    • opinion-alignment vulnerabilities-data model-adaptation self-instruction alignment
    • language-reasoning
    • exam-evaluation
    • task-performance
• Miscellaneous
• Bibliography