Papers › CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language...

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

11 Sep 2019IJCNLP 2019 11arXiv:1909.05378archive 2025-07-28

Tao Yu, Rui Zhang, He Yang Er, Suyi Li, Eric Xue, Bo Pang, Xi Victoria Lin, Yi Chern Tan, Tianze Shi, Zihan Li, Youxuan Jiang, Michihiro Yasunaga, Sungrok Shim, Tao Chen, Alexander Fabbri, Zifan Li, Luyao Chen, Yuwen Zhang, Shreya Dixit, Vincent Zhang, Caiming Xiong, Richard Socher, Walter S. Lasecki, Dragomir Radev

We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained from a Wizard-of-Oz (WOZ) collection of 3k dialogues querying 200 complex DBs spanning 138 domains. Each dialogue simulates a real-world DB query scenario with a crowd worker as a user exploring the DB and a SQL expert retrieving answers with SQL, clarifying ambiguous questions, or otherwise informing of unanswerable questions. When user questions are answerable by SQL, the expert describes the SQL and execution results to the user, hence maintaining a natural interaction flow. CoSQL introduces new challenges compared to existing task-oriented dialogue datasets:(1) the dialogue states are grounded in SQL, a domain-independent executable representation, instead of domain-specific slot-value pairs, and (2) because testing is done on unseen databases, success requires generalizing to new domains. CoSQL includes three tasks: SQL-grounded dialogue state tracking, response generation from query results, and user dialogue act prediction. We evaluate a set of strong baselines for each task and show that CoSQL presents significant challenges for future research. The dataset, baselines, and leaderboard will be released at https://yale-lily.github.io/cosql.

PaperPDFConference PDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="1909.05378")

Code

Syntology Ran 1 of 11 code samples harvested from 1 repository linked to this paper; 10 have no recorded run. Of those that ran: 1 ran · our draft was wrong.

By repository: community (archive-listed): 11 samples from 1 repository, 1 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

ryanzhumich/editsql officialmentioned on GitHubpytorch report
amolk/editsql mentioned on GitHubpytorchMIT report
ryanzhumich/sparc_atis_pytorch mentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

11 samples harvested; 1 ran; 0 honoured the contract we drafted; 10 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · our draft was wrong
10unverified

Licence: 0 of the 11 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from amolk/editsql. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

encode_snippets_with_states amolk/editsql/model/model.py community (archive-listed) ran · our draft was wrong MIT (permissive) · 0bff7fccef337b38 · report
compute_loss amolk/editsql/model/torch_utils.py community (archive-listed) unverified MIT (permissive) · 7e2d038f758acc4a · report
flatten_distribution amolk/editsql/model/decoder.py community (archive-listed) unverified MIT (permissive) · c59f3f02b15d3770 · report
gen_l_hpu amolk/editsql/model/utils_bert.py community (archive-listed) unverified MIT (permissive) · 8a55b7ef1c467cea · report
generate_inputs amolk/editsql/model/utils_bert.py community (archive-listed) unverified MIT (permissive) · 0ef533abd86a2b26 · report
get_bert amolk/editsql/model/utils_bert.py community (archive-listed) unverified MIT (permissive) · 9ac04740fba8c9cf · report
get_seq_from_scores amolk/editsql/model/torch_utils.py community (archive-listed) unverified MIT (permissive) · 03149eb9ca360505 · report
linear_layer amolk/editsql/model/torch_utils.py community (archive-listed) unverified MIT (permissive) · 4f3f1f5678f97059 · report
score_query_tokens amolk/editsql/model/token_predictor.py community (archive-listed) unverified MIT (permissive) · 004b8e1db7db5c18 · report
score_schema_tokens amolk/editsql/model/token_predictor.py community (archive-listed) unverified MIT (permissive) · c3efa7d8a524d46d · report
score_snippets amolk/editsql/model/token_predictor.py community (archive-listed) unverified MIT (permissive) · 26a5daacb4d2f144 · report

Tasks

Dialogue State TrackingResponse GenerationText to SQLText-To-SQL

Datasets

Introduced by this paper, per the archive.

CoSQL

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Dialogue State Tracking CoSQL SyntaxSQL-con interaction match accuracy 2.2 #8 of 9 Archive leaderboard report
Dialogue State Tracking CoSQL SyntaxSQL-con question match accuracy 14.1 #8 of 9 Archive leaderboard report
Dialogue State Tracking CoSQL CD-Seq2seq interaction match accuracy 2.6 #9 of 9 Archive leaderboard report
Dialogue State Tracking CoSQL CD-Seq2seq question match accuracy 13.9 #9 of 9 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections