{"list":"other","total":53,"rows":[{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2307.09288","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","created":"2023-07-18","cited_by_count":13028},{"id":"1412.6572","title":"Explaining and Harnessing Adversarial Examples","created":"2014-12-20","cited_by_count":7364},{"id":"1910.13461","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","created":"2019-10-29","cited_by_count":5893},{"id":"1904.09675","title":"BERTScore: Evaluating Text Generation with BERT","created":"2019-04-21","cited_by_count":5512},{"id":"2205.01068","title":"OPT: Open Pre-trained Transformer Language Models","created":"2022-05-02","cited_by_count":3512},{"id":"1904.09751","title":"The Curious Case of Neural Text Degeneration","created":"2019-04-22","cited_by_count":2916},{"id":"2111.09543","title":"DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing","created":"2021-11-18","cited_by_count":1254},{"id":"1912.08777","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","created":"2019-12-18","cited_by_count":1102},{"id":"2112.04359","title":"Ethical and social risks of harm from Language Models","created":"2021-12-08","cited_by_count":966},{"id":"2204.07705","title":"Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks","created":"2022-04-16","cited_by_count":868},{"id":"2305.01937","title":"Can Large Language Models Be an Alternative to Human Evaluations?","created":"2023-05-03","cited_by_count":734},{"id":"2301.11305","title":"DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature","created":"2023-01-26","cited_by_count":726},{"id":"2106.11520","title":"BARTScore: Evaluating Generated Text as Text Generation","created":"2021-06-22","cited_by_count":722},{"id":"1907.11932","title":"Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment","created":"2019-07-27","cited_by_count":671},{"id":"1905.12616","title":"Defending Against Neural Fake News","created":"2019-05-29","cited_by_count":559},{"id":"1908.09203","title":"Release Strategies and the Social Impacts of Language Models","created":"2019-08-24","cited_by_count":513},{"id":"1908.04319","title":"Neural Text Generation with Unlikelihood Training","created":"2019-08-12","cited_by_count":503},{"id":"1906.04043","title":"GLTR: Statistical Detection and Visualization of Generated Text","created":"2019-06-10","cited_by_count":496},{"id":"2301.07597","title":"How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection","created":"2023-01-18","cited_by_count":481},{"id":"2102.01454","title":"MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers","created":"2021-02-02","cited_by_count":470},{"id":"2303.13408","title":"Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense","created":"2023-03-23","cited_by_count":429},{"id":"2212.09689","title":"Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor","created":"2022-12-19","cited_by_count":397},{"id":"1812.05271","title":"TextBugger: Generating Adversarial Text Against Real-world Applications","created":"2018-12-13","cited_by_count":381},{"id":"2307.15593","title":"Robust Distortion-free Watermarks for Language Models","created":"2023-07-28","cited_by_count":320},{"id":"2306.17439","title":"Provable Robust Watermarking for AI-Generated Text","created":"2023-06-30","cited_by_count":299},{"id":"2310.05130","title":"Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature","created":"2023-10-08","cited_by_count":287},{"id":"1804.06059","title":"Adversarial Example Generation with Syntactically Controlled Paraphrase Networks","created":"2018-04-17","cited_by_count":286},{"id":"2001.04063","title":"ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training","created":"2020-01-13","cited_by_count":222},{"id":"2306.05540","title":"DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text","created":"2023-05-23","cited_by_count":210},{"id":"2307.03838","title":"RADAR: Robust AI-Text Detection via Adversarial Learning","created":"2023-07-07","cited_by_count":190},{"id":"2305.14902","title":"M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection","created":"2023-05-24","cited_by_count":121},{"id":"1903.11508","title":"Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems","created":"2019-03-27","cited_by_count":101},{"id":"1811.02549","title":"Language GANs Falling Short","created":"2018-11-06","cited_by_count":97},{"id":"2303.14822","title":"MGTBench: Benchmarking Machine-Generated Text Detection","created":"2023-03-26","cited_by_count":93},{"id":"2107.01294","title":"Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text","created":"2021-07-02","cited_by_count":89},{"id":"2304.04736","title":"On the Possibilities of AI-Generated Text Detection","created":"2023-04-10","cited_by_count":88},{"id":"2210.07700","title":"Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey","created":"2022-10-14","cited_by_count":80},{"id":"2212.12672","title":"Real or Fake Text?: Investigating Human Ability to Detect Boundaries Between Human-Written and Machine-Generated Text","created":"2022-12-24","cited_by_count":63},{"id":"2401.12970","title":"Raidar: geneRative AI Detection viA Rewriting","created":"2024-01-23","cited_by_count":52},{"id":"2402.11399","title":"k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text","created":"2024-02-17","cited_by_count":51},{"id":"2212.10020","title":"On the Blind Spots of Model-Based Evaluation Metrics for Text Generation","created":"2022-12-20","cited_by_count":49},{"id":"2305.09859","title":"Smaller Language Models are Better Black-box Machine-Generated Text Detectors","created":"2023-05-17","cited_by_count":35},{"id":"2309.02731","title":"HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus","created":"2023-09-06","cited_by_count":35},{"id":"2212.10341","title":"CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning","created":"2022-12-20","cited_by_count":33},{"id":"2009.07243","title":"A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation","created":"2020-09-15","cited_by_count":28},{"id":"2402.00371","title":"What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection","created":"2024-02-01","cited_by_count":25},{"id":"2310.05165","title":"On the Zero-Shot Generalization of Machine-Generated Text Detectors","created":"2023-10-08","cited_by_count":11},{"id":"2402.00263","title":"Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better","created":"2024-02-01","cited_by_count":11},{"id":"2304.14395","title":"string2string: A Modern Python Library for String-to-String Algorithms","created":"2023-04-27","cited_by_count":9},{"id":"2312.12918","title":"Assaying on the Robustness of Zero-Shot Machine-Generated Text Detectors","created":"2023-12-20","cited_by_count":8}],"next_cursor":null}