All datasets / alexchern5757
alexchern5757/groundhog_reddit
The declared licence (mit) is classified as permissive.
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Citation text from the card
@inproceedings{chernyavskiy-etal-2024-groundhog,
title = "{G}round{H}og: Dialogue Generation using Multi-Grained Linguistic Input",
author = "Chernyavskiy, Alexander and
Ostyakova, Lidiia and
Ilvovsky, Dmitry",
editor = "Strube, Michael and
Braud, Chloe and
Hardmeier, Christian and
Li, Junyi Jessy and
Loaiciga, Sharid and
Zeldes, Amir and
Li, Chuyuan",
booktitle = "Proceedings of the 5th Workshop on Computational Approaches to Discourse (CODI 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.codi-1.14",
pages = "149--160",
abstract = "Recent language models have significantly boosted conversational AI by enabling fast and cost-effective response generation in dialogue systems. However, dialogue systems based on neural generative approaches often lack truthfulness, reliability, and the ability to analyze the dialogue flow needed for smooth and consistent conversations with users. To address these issues, we introduce GroundHog, a modified BART architecture, to capture long multi-grained inputs gathered from various factual and linguistic sources, such as Abstract Meaning Representation, discourse relations, sentiment, and grounding information. For experiments, we present an automatically collected dataset from Reddit that includes multi-party conversations devoted to
The same facts for your agent
A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.
dataset_licence({ "id": "alexchern5757/groundhog_reddit" })
signal: "permissive"
stated_licence: "mit"
sources: 0