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Response Generation datasets

archive 2025-07-28

8 datasets carry the task tag "Response Generation" (the task itself: Response Generation), ordered by the archive's paper count. Page 1 of 1: 8 shown of 8. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

All 12,172 Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Response Generation 8

Response Generation datasets 1–8 of 8

ProsocialDialog
Most existing dialogue systems fail to respond properly to potentially unsafe user utterances by either ignoring or passively agreeing with them.
TextsDialogDialogue UnderstandingDialogue GenerationOpen-Domain DialogResponse GenerationDialogue Safety Prediction
13 papers · 1 benchmark
SIMMC2.0
Next generation task-oriented dialog systems need to understand conversational contexts with their perceived surroundings, to effectively help users in the real-world multimodal environment.
ImagesTextsDialogue State TrackingResponse Generation
13 papers · 2 benchmarks
ComFact
ComFact is a benchmark for commonsense fact linking, where models are given contexts and trained to identify situationally-relevant commonsense knowledge from KGs.
TextsKnowledge GraphsRetrievalResponse Generation
5 papers · 0 benchmarks
KETOD (Knowledge-Enriched Task-Oriented Dialogue)
KETOD (Knowledge-Enriched Task-Oriented Dialogue) is a dataset containing system responses designed for enriching task-oriented dialogues with chit-chat based on relevant entity knowledge.
TextsResponse Generation
5 papers · 0 benchmarks
MMConv
The main goal of the data collection is to acquire highly natural conversations that cover a wide variety of styles and scenarios.
ImagesTextsDialogue State TrackingResponse Generation
3 papers · 2 benchmarks
ArgSciChat
ArgSciChat is an argumentative dialogue dataset.
TextsResponse GenerationFact Selection
1 paper · 2 benchmarks
Comet
Comet is a dataset which contains 11.5k user-assistant dialogs (totalling 103k utterances), grounded in simulated personal memory graphs.
TextsCoreference ResolutionResponse Generation
1 paper · 0 benchmarks
LLMafia
To evaluate our proposed strategy of asynchronous communication for LLMs, we run games of Mafia with human players, incorporating an LLM-based agent as an additional player, within an asynchronous chat environment.
TextsText GenerationDialogue GenerationTask-Oriented Dialogue SystemsGesture GenerationReal-Time Strategy GamesMulti-Human Parsing+14 tasks
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.