Comparison of Diverse Decoding Methods from Conditional Language Models
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Abstract (arXiv)
While conditional language models have greatly improved in their ability to output high-quality natural language, many NLP applications benefit from being able to generate a diverse set of candidate sequences. Diverse decoding strategies aim to, within a given-sized candidate list, cover as much of the space of high-quality outputs as possible, leading to improvements for tasks that re-rank and combine candidate outputs. Standard decoding methods, such as beam search, optimize for generating high likelihood sequences rather than diverse ones, though recent work has focused on increasing diversity in these methods. In this work, we perform an extensive survey of decoding-time strategies for generating diverse outputs from conditional language models. We also show how diversity can be improved without sacrificing quality by over-sampling additional candidates, then filtering to the desired number.
Key facts. Cited by 78 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jun 2019.
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Citing papers per year: 2021: 12; 2022: 11; 2023: 11; 2024: 16; 2025: 19; 2026: 9.
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50 most cited of 78 All 78 (JSON)
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- 2025Local Normalization Distortion and the Thermodynamic Formalism of Decoding Strategies for Large Language Models27 Mar 2025
- 2025Modifying Large Language Model Post-Training for Diverse Creative Writing21 Mar 2025
- 2025DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation19 Feb 2025
- 2025Efficient Beam Search for Large Language Models Using Trie-Based Decoding31 Jan 2025
- 2025Reference-free Evaluation Metrics for Text Generation: A Survey21 Jan 2025
- 2024GeAR: Graph-enhanced Agent for Retrieval-augmented Generation24 Dec 2024
- 2024Quasi-random Multi-Sample Inference for Large Language Models9 Nov 2024
- 2024Improving Structural Diversity of Blackbox LLMs via Chain-of-Specification Prompting12 Aug 2024
- 2024Representation Bias of Adolescents in AI: A Bilingual, Bicultural Study4 Aug 2024
- 2024Evaluating Diversity in Automatic Poetry Generation21 Jun 2024
- 2024Improving Uncertainty Estimation through Semantically Diverse Language Generation6 Jun 2024
- 2024Guiding and Diversifying LLM-Based Story Generation via Answer Set Programming1 Jun 2024
- 2024SED: Self-Evaluation Decoding Enhances Large Language Models for Better Generation26 May 2024
- 2024Not Just Novelty: A Longitudinal Study on Utility and Customization of an AI Workflow15 Feb 2024
- 2024Generating Diverse Translation with Perturbed kNN-MT14 Feb 2024
- 2024A Thorough Examination of Decoding Methods in the Era of LLMs10 Feb 2024
- 2024Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs8 Feb 2024
- 2024ConvoSense: Overcoming Monotonous Commonsense Inferences for Conversational AI27 Jan 2024
- 2024ARGS: Alignment as Reward-Guided Search23 Jan 2024
- 2024ELLA-V: Stable Neural Codec Language Modeling with Alignment-guided Sequence Reordering14 Jan 2024
- 2024Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding10 Jan 2024
- 2023PathFinder: Guided Search over Multi-Step Reasoning Paths8 Dec 2023
- 2023Interpretation modeling: Social grounding of sentences by reasoning over their implicit moral judgments27 Nov 2023
- 2023The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text16 Nov 2023
- 2023Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects -- A Survey15 Nov 2023
- 2023Closing the Curious Case of Neural Text Degeneration2 Oct 2023
- 2023A Methodology for Generative Spelling Correction via Natural Spelling Errors Emulation across Multiple Domains and Languages18 Aug 2023
50 newest of 78 All 78 (JSON)
- 2021NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristicscited by 153
- 2022LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Taskscited by 146
- 2023Towards Making the Most of ChatGPT for Machine Translationcited by 138
- 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
- 2024A Thorough Examination of Decoding Methods in the Era of LLMscited by 112
- 2023The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Textcited by 97
- 2022On Decoding Strategies for Neural Text Generatorscited by 89
- 2021Sparks: Inspiration for Science Writing using Language Modelscited by 80
- 2025Jointly Reinforcing Diversity and Quality in Language Model Generationscited by 79
- 2024ELLA-V: Stable Neural Codec Language Modeling with Alignment-guided Sequence Reorderingcited by 50
- 2024Improving Uncertainty Estimation through Semantically Diverse Language Generationcited by 34
- 2023Closing the Curious Case of Neural Text Degenerationcited by 30
12 most cited of 67 All 67 (JSON)
- 2026Improving the Diversity of LLM Outputs without a Trade-off27 Sep 2026
- 2026Evaluating Multiple LLM Generations with Validated Task Coverage25 Aug 2026
- 2026TalkMatrix: Generating Character Dialogue that is Both Consistent and Diverse20 Jul 2026
- 2026A Generalized Formalism of Auto-Regressive Decoding for Speech Processing16 Jun 2026
- 2026Anchorless Diversification for Parallel LLM Ideation28 May 2026
- 2026AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing25 May 2026
- 2026IntentCoding: Amplifying User Intent in Code Generation20 Jan 2026
- 2025PARAN: Persona-Augmented Review ANswering system on Food Delivery Review Dataset10 Dec 2025
- 2025Efficient semantic uncertainty quantification in language models via diversity-steered sampling24 Oct 2025
- 2025Jointly Reinforcing Diversity and Quality in Language Model Generations2 Sep 2025
- 2025A survey of diversity quantification in natural language processing: The why, what, where and how28 Jul 2025
- 2025E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI24 Jul 2025
12 newest of 67 All 67 (JSON)