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Paper Citation Record · LEDGER

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data

As of 4 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 1 inbound Pith citation observation for arXiv:2603.07841.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2603.07841 v2

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:39:41.316604Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T15:41:51.078898Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T15:44:48.313235Z

Reference resolution

75 of 75 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07c09ce4-982b-4bef-a060-fc8b724cc2a4 · outbound

This paper cites The dawn of natural language to sql: Are we fully ready?.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data The dawn of natural language to sql: Are we fully ready?

Reference 1

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source=pdf_text observed=2026-08-02T18:39:32.772734Z digest=sha256:af0746b493b7638f79e9f512945218703d383cfa3186e47a72b823c04e6cd591

Observation 1202f5a5-b513-4441-a755-f4b735421548 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 2

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source=pdf_text observed=2026-08-02T18:39:32.867967Z digest=sha256:293440c299145b6c888d805f9aa450462822da2b0f32f4d56b242018e9a3807f

Observation 5868c4c3-be93-41ea-8a32-1a41a3d0fc21 · outbound

This paper cites SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

Reference 3

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source=pdf_text observed=2026-08-02T18:39:32.944351Z digest=sha256:173a6812d77b80973b6a04ac3b702961ead75125aad852dcc9a0b6711f840d1c

Observation 053f0928-804c-4789-afdd-86f19977e093 · outbound

This paper cites TypeSQL: Knowledge- based type-aware neural text-to-SQL generation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data TypeSQL: Knowledge- based type-aware neural text-to-SQL generation,

Reference 4

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source=pdf_text observed=2026-08-02T18:39:32.998864Z digest=sha256:86eac7109019631e69fd8c71b6d3c0e484ef0a355c5b9f6ec0fcfb71d6d94051

Observation 6a3ed6f2-cf9a-4681-9b5a-3ca9455762b1 · outbound

This paper cites SyntaxSQLNet: Syntax tree networks for complex and cross-domain text-to-SQL task,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SyntaxSQLNet: Syntax tree networks for complex and cross-domain text-to-SQL task,

Reference 5

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source=pdf_text observed=2026-08-02T18:39:33.050050Z digest=sha256:32803f8a267ce2ced6c5ab272d68415b10abe2cf1c623e479e9d10ed3afd776a

Observation 603d7bf0-b8c3-4215-82c9-c72515a00750 · outbound

This paper cites Editing-based SQL query generation for cross-domain context-dependent questions,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Editing-based SQL query generation for cross-domain context-dependent questions,

Reference 6

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source=pdf_text observed=2026-08-02T18:39:33.098760Z digest=sha256:48e7c933d74a70ce4f9c65183e51bd55f8735ff2d326d61017639ceb51109f22

Observation a8c5afc0-577b-472f-be76-1583aaddac24 · outbound

This paper cites To- wards complex text-to-SQL in cross-domain database with intermediate representation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data To- wards complex text-to-SQL in cross-domain database with intermediate representation,

Reference 7

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source=pdf_text observed=2026-08-02T18:39:33.160243Z digest=sha256:61cbdf17071c8e5013418f918fc0b0555f2b1ca8669da6626f23c1052ccd472e

Observation 63d33d8a-c4ce-4c8f-b355-408dfb6fa8c0 · outbound

This paper cites RAT-SQL: Relation-aware schema encoding and linking for text-to-SQL parsers,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data RAT-SQL: Relation-aware schema encoding and linking for text-to-SQL parsers,

Reference 8

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source=pdf_text observed=2026-08-02T18:39:33.217219Z digest=sha256:e97a535aff0a5a2941388a8194b4f0dec8a84f909244417045df767b821eec56

Observation 5483ae2d-d2b0-48f9-a847-fba1c26e7770 · outbound

This paper cites Bridging textual and tabular data for cross-domain text-to-SQL semantic parsing,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Bridging textual and tabular data for cross-domain text-to-SQL semantic parsing,

Reference 9

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source=pdf_text observed=2026-08-02T18:39:33.294166Z digest=sha256:8dd0202b7801fb01d42b5bc459af1e53829e94baa68c1b66daefc921caa8ccad

Observation e67b3f0d-9987-47c1-a053-2d15ffc4a1ed · outbound

This paper cites SmBoP: Semi-autoregressive bottom-up se- mantic parsing,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SmBoP: Semi-autoregressive bottom-up se- mantic parsing,

Reference 10

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source=pdf_text observed=2026-08-02T18:39:33.374273Z digest=sha256:4e02e757931cdb99aa5d6e81edcfc67f30139212a338a87e520ea572fd5efe45

Observation 6c6eecc1-1442-4979-9b45-8fc1f2b605c6 · outbound

This paper cites LGESQL: Line graph enhanced text-to-SQL model with mixed local and non-local relations,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data LGESQL: Line graph enhanced text-to-SQL model with mixed local and non-local relations,

Reference 11

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source=pdf_text observed=2026-08-02T18:39:33.456786Z digest=sha256:e3b7d0c70944b28598fa3eb9c277ce2a615a0f4b2dafcd3c983d003d0d5880c4

Observation 6e64e266-c7ae-488e-a5ad-67ef8b772684 · outbound

This paper cites Gra{pp}a: Grammar-augmented pre-training for table semantic parsing,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Gra{pp}a: Grammar-augmented pre-training for table semantic parsing,

Reference 12

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source=pdf_text observed=2026-08-02T18:39:33.523021Z digest=sha256:79f3e16413a12c36bc2205f9a7d0adc849e5e7e71045262508889234c36ae78a

Observation bc6acdb3-3436-4304-b581-5eb6263cbacc · outbound

This paper cites PICARD: Parsing in- crementally for constrained auto-regressive decoding from language models,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data PICARD: Parsing in- crementally for constrained auto-regressive decoding from language models,

Reference 13

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source=pdf_text observed=2026-08-02T18:39:33.651687Z digest=sha256:9f3c97458b016f44e72c7c8165d943f15aa46d6f8ad2f838ce0f7764f96457d2

Observation fa427ed9-e335-4ba0-8296-596c755c7911 · outbound

This paper cites DIN-SQL: Decomposed in-context learning of text-to-SQL with self-correction,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data DIN-SQL: Decomposed in-context learning of text-to-SQL with self-correction,

Reference 14

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source=pdf_text observed=2026-08-02T18:39:33.710665Z digest=sha256:453ad1c35680fdf444157f11974ae4c7f317a6d41e94cea2818718f136b41585

Observation cb156028-2860-48d3-953a-beace5097580 · outbound

This paper cites Text- to-sql empowered by large language models: A benchmark evaluation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Text- to-sql empowered by large language models: A benchmark evaluation,

Reference 15

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source=pdf_text observed=2026-08-02T18:39:33.823343Z digest=sha256:7edf805a519d56128ac93a6c97393710f5b9616eda23823b384d84352889af64

Observation 33605d56-34c6-43cd-84a7-722623f526fc · outbound

This paper cites CHESS: Contextual Harnessing for Efficient SQL Synthesis.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 16

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source=pdf_text observed=2026-08-02T18:39:33.980750Z digest=sha256:161ba790821ba851242b8f978444e7224a422d88fdbcfa8aec99d9227607d71d

Observation 3be4cde5-3af2-4071-bbdc-8c5abf2fa770 · outbound

This paper cites How to answer secure and private SQL queries?.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data How to answer secure and private SQL queries?

Reference 17

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source=pdf_text observed=2026-08-02T18:39:34.206703Z digest=sha256:3d9770a502e30882c9e49f130be5bc8269d2877c68fac88308ad88d8a041ec97

Observation 0c961342-6ffc-43c2-a003-773978bf40c3 · outbound

This paper cites Lampat: Low-rank adaption for multilingual paraphrasing using adversarial training,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Lampat: Low-rank adaption for multilingual paraphrasing using adversarial training,

Reference 18

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source=pdf_text observed=2026-08-02T18:39:34.377665Z digest=sha256:98bdbb9d6b08713798e79be0241df4074b82b5d1455204bd8fc80f71bc58f7d9

Observation 174c535a-b878-43a1-9f29-bd1510addd95 · outbound

This paper cites UniBridge: A unified approach to cross- lingual transfer learning for low-resource languages,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data UniBridge: A unified approach to cross- lingual transfer learning for low-resource languages,

Reference 19

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source=pdf_text observed=2026-08-02T18:39:34.573043Z digest=sha256:d4aede27976d72635ef520f8298e03a900997b995885ce64a9b2805f74147db2

Observation bbb7d609-e10b-4877-9baf-585e8e99cb3b · outbound

This paper cites Resdsql: Decoupling schema linking and skeleton parsing for text-to-sql,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Resdsql: Decoupling schema linking and skeleton parsing for text-to-sql,

Reference 20

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source=pdf_text observed=2026-08-02T18:39:34.794936Z digest=sha256:4c4c2a113f2d5df3760e31737c3a3943db789ac2d9eb2ed357a9aa5d4f8d62dc

Observation c7ddca6f-2705-4779-92d9-6f98f52a4be5 · outbound

This paper cites CHASE-SQL: Multi-path reasoning and preference optimized candidate selection in text-to-SQL,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data CHASE-SQL: Multi-path reasoning and preference optimized candidate selection in text-to-SQL,

Reference 21

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source=pdf_text observed=2026-08-02T18:39:34.990884Z digest=sha256:32ba72ced10880dab4ed05010457f14af2951bc3de81b8b1f67e9f039d19ff10

Observation eb796730-4322-4aad-abb3-de06b9921841 · outbound

This paper cites Csc-sql: Corrective self-consistency in text-to- sql via reinforcement learning,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Csc-sql: Corrective self-consistency in text-to- sql via reinforcement learning,

Reference 22

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source=pdf_text observed=2026-08-02T18:39:35.157669Z digest=sha256:8572fa2bb658adfac0437ca9818d5d1a2f8990258bfa30a8f349050a1744dc7d

Observation b747c33f-c27d-494a-bfbe-9a6a1ac39cde · outbound

This paper cites Alpha- SQL: Zero-shot text-to-SQL using monte carlo tree search,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Alpha- SQL: Zero-shot text-to-SQL using monte carlo tree search,

Reference 23

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source=pdf_text observed=2026-08-02T18:39:35.279769Z digest=sha256:7b46da8d15ea47172f162f80a499da12bdd74b9604a3b93ff30b84ca4843ae20

Observation 26f9f3c9-47b2-41bd-83fc-a96ab2849cb9 · outbound

This paper cites Grounding natural language to SQL translation with data-based self-explanations,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Grounding natural language to SQL translation with data-based self-explanations,

Reference 24

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source=pdf_text observed=2026-08-02T18:39:35.456560Z digest=sha256:aa9403f78f9ba1c4cc1dbc3cad91ecd7cf8493c47ad0e28769721f58d34b1f34

Observation 54f25c97-e497-4180-b84a-32e10eda3419 · outbound

This paper cites Machine learning inference pipeline execution using pure SQL based on operator fusion,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Machine learning inference pipeline execution using pure SQL based on operator fusion,

Reference 25

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source=pdf_text observed=2026-08-02T18:39:35.514386Z digest=sha256:2b1dd38b43517af0f0f390477d694cddb22a404170c02ecdbfbc7f0338c22df0

Observation 31c1b549-2555-4703-b109-0040f18527e9 · outbound

This paper cites AID-SQL: adaptive in-context learning of text-to-sql with difficulty-aware instruction and retrieval-augmented generation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data AID-SQL: adaptive in-context learning of text-to-sql with difficulty-aware instruction and retrieval-augmented generation,

Reference 26

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source=pdf_text observed=2026-08-02T18:39:35.559081Z digest=sha256:33ad4a251d5ceebac7f2e0ff93e3508345f2e1b741055b6090127ea4489d6a54

Observation 67524ef4-8b66-41d1-84ca-7194472ad2cc · outbound

This paper cites AgenticData: An Agentic Data Analytics System for Heterogeneous Data.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data AgenticData: An Agentic Data Analytics System for Heterogeneous Data

Reference 27

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source=pdf_text observed=2026-08-02T18:39:35.581469Z digest=sha256:4b52a8ce51b03e2ff392476e08a889c86c30a68f153e032ff4e80cea0e68a4f5

Observation e2f9b57f-24c7-4909-a810-69c1b2f139aa · outbound

This paper cites RefoRCE: A text-to-SQL agent with self-refinement, format restriction, and column exploration,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data RefoRCE: A text-to-SQL agent with self-refinement, format restriction, and column exploration,

Reference 28

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source=pdf_text observed=2026-08-02T18:39:35.633695Z digest=sha256:8d0921abe63fba30139d56e10a5ecf7e05f51448b5c93d6fa836b012b3af52cd

Observation 121774b4-3f79-4479-89a3-f5f26cef49e7 · outbound

This paper cites Omnisql: Synthesizing high-quality text-to-sql data at scale,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Omnisql: Synthesizing high-quality text-to-sql data at scale,

Reference 29

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source=pdf_text observed=2026-08-02T18:39:35.676004Z digest=sha256:f69af41aae9f0f96b90ab2beb2e5157f941322273afd802ecdb769b7657fd187

Observation 1352d12a-e360-4bb3-a6eb-aec384ef2a3a · outbound

This paper cites Multilingual text-to-sql: Benchmarking the limits of language models with collaborative language agents,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Multilingual text-to-sql: Benchmarking the limits of language models with collaborative language agents,

Reference 30

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source=pdf_text observed=2026-08-02T18:39:35.712320Z digest=sha256:74526a2c645267d60185a15e5cf6b48d00e6d6d09694721047122769e7360493

Observation b4a0172f-67e7-4559-8a45-b19469c740c5 · outbound

This paper cites Jacobsson.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Jacobsson

Reference 31

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source=pdf_text observed=2026-08-02T18:39:35.750068Z digest=sha256:81602c5e3b028698809760fe0e6917f4ea45e825faea5b2c730159ebd7689d7d

Observation defd7372-2655-4e1d-a045-10838ce77d52 · outbound

This paper cites Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task,

Reference 32

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source=pdf_text observed=2026-08-02T18:39:35.942932Z digest=sha256:772e20fafa2b4e1113ca2d660f31086007b32f4aa655d76c47e3c0d555d97e86

Observation 56d2c5a2-cff8-4bef-92ef-976d4ddb288a · outbound

This paper cites Sparc: Cross-domain semantic parsing in context,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Sparc: Cross-domain semantic parsing in context,

Reference 33

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source=pdf_text observed=2026-08-02T18:39:36.034626Z digest=sha256:bbfdbbc4234155167bf4629c9ea818295b206928d0e8ab2cb780b04f6f766b4d

Observation c346af49-7ab6-41ae-a6cd-138a4f66d945 · outbound

This paper cites Cosql: A conversational text- to-sql challenge towards cross-domain natural language interfaces to databases,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Cosql: A conversational text- to-sql challenge towards cross-domain natural language interfaces to databases,

Reference 34

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source=pdf_text observed=2026-08-02T18:39:36.150832Z digest=sha256:f22750ecd4b216594e09af3770e3d99fff2515355eea8c433ce5922f2cc63e93

Observation 57507061-049e-4f4e-a349-fb1d2965d2b5 · outbound

This paper cites Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,

Reference 35

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source=pdf_text observed=2026-08-02T18:39:36.251162Z digest=sha256:f3a1cf3d13fd565656d9746dbd02b3882083acf024e43c8a04a9298eb79f624a

Observation 21cd6d72-90d3-4283-be8c-57e1e4a4e407 · outbound

This paper cites Spider 2.0: Evaluating language models on real-world enterprise text-to-SQL workflows,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Spider 2.0: Evaluating language models on real-world enterprise text-to-SQL workflows,

Reference 36

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source=pdf_text observed=2026-08-02T18:39:36.394214Z digest=sha256:4024602ad82760112a515e17c2972b5ff2c36150460d1fdb4eb89e501b872966

Observation 86ef3cd9-2a91-4573-bcef-c3b50c424c36 · outbound

This paper cites Estimating large language model capabilities without labeled test data,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Estimating large language model capabilities without labeled test data,

Reference 37

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Observation 29e1475a-ee9e-433c-a47d-abcb34e28861 · outbound

This paper cites SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models,

Reference 38

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source=pdf_text observed=2026-08-02T18:39:36.627540Z digest=sha256:1bb89745273e68befd247645c4b2e55b63f69585a5c50ffaa6efcbd9868d1b64

Observation 21fe3fb7-7e63-419c-9f5a-faf40d2e45cf · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Detecting hallucinations in large language models using semantic entropy,

Reference 39

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source=pdf_text observed=2026-08-02T18:39:36.764186Z digest=sha256:1a5ea1c2173e3955ee9b8ff7d1f4a1ba7714d784f92b464fe3bd7569f63ca1a1

Observation 88eaec25-07a0-4c4f-bd39-50cc85d7f8f2 · outbound

This paper cites Autoeval done right: Using synthetic data for model evaluation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Autoeval done right: Using synthetic data for model evaluation,

Reference 40

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source=pdf_text observed=2026-08-02T18:39:36.841370Z digest=sha256:750154575c5b4dadde9a3c3d9f0a0ea55503f826f87d461570e65e74abe36697

Observation 7ed38252-97df-4c6e-88e4-fc3d69d03288 · outbound

This paper cites Prediction-powered inference,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Prediction-powered inference,

Reference 41

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source=pdf_text observed=2026-08-02T18:39:36.974271Z digest=sha256:ba90e9e25fc2fe81d062209acbc591c502f80eb4204d085960b822047e1c3029

Observation eedf78a3-1d9a-46ff-927c-1f5617f21569 · outbound

This paper cites Leveraging unlabeled data to predict out-of-distribution performance,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Leveraging unlabeled data to predict out-of-distribution performance,

Reference 42

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source=pdf_text observed=2026-08-02T18:39:37.134328Z digest=sha256:db2b29e70ae97a60f157031e55f8e92a01daeeaaed071754842a61bd58c54e84

Observation 51a253a6-f856-4dd0-9500-d3c3d80af3fc · outbound

This paper cites Predicting with confidence on unseen distributions,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Predicting with confidence on unseen distributions,

Reference 43

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source=pdf_text observed=2026-08-02T18:39:37.298968Z digest=sha256:edc5b062023ea96fac24bc49b915bd608c88f3d2237b85195787090b7df0d4b4

Observation c4c13444-028a-4b66-ac6d-9dd182b92cf0 · outbound

This paper cites Nl2sql-bugs: A benchmark for detecting semantic errors in nl2sql translation,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Nl2sql-bugs: A benchmark for detecting semantic errors in nl2sql translation,

Reference 44

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source=pdf_text observed=2026-08-02T18:39:37.464847Z digest=sha256:d654321298470e0904593ead6ce58cbb824613087d05003f75f97767ef5142d3

Observation 3cc1b5db-bc06-4510-98af-a94614e765a3 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 45

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source=pdf_text observed=2026-08-02T18:39:37.578381Z digest=sha256:536c1c9927a92b7d6471f2b63be7d676be0a95319e27a401db27e22b5c0fcf04

Observation d2514b1a-2d95-4555-bbb1-334724510e0d · outbound

This paper cites TabLib: A Dataset of 627M Tables with Context.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data TabLib: A Dataset of 627M Tables with Context

Reference 46

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source=pdf_text observed=2026-08-02T18:39:37.752511Z digest=sha256:bbf7b4c2ead16f1dfb8311e13c65fc5ffbe29c402c4e6f15b064e4b1c2504101

Observation 1ae63f45-aa34-40b3-8499-48e3e4cc0dff · outbound

This paper cites KaggleDBQA: Realistic evaluation of text-to-SQL parsers,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data KaggleDBQA: Realistic evaluation of text-to-SQL parsers,

Reference 47

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source=pdf_text observed=2026-08-02T18:39:37.866666Z digest=sha256:a195db81362dea6d6427ce929376b39412eef57d881441ee29999f3ac45594c7

Observation f368c44a-56e0-4681-af13-233cbc86859a · outbound

This paper cites SQLForge: Synthesizing reliable and diverse data to enhance text-to-SQL reasoning in LLMs,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SQLForge: Synthesizing reliable and diverse data to enhance text-to-SQL reasoning in LLMs,

Reference 48

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source=pdf_text observed=2026-08-02T18:39:38.074736Z digest=sha256:459c64e88ee4ea12bae291408a65caab2fb9643f034a883993f57453a3c20e1c

Observation 5e44003d-2fc6-4ada-80da-af2393913983 · outbound

This paper cites Parsql: Enhancing text-to-sql through sql parsing and reasoning,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Parsql: Enhancing text-to-sql through sql parsing and reasoning,

Reference 49

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source=pdf_text observed=2026-08-02T18:39:38.197809Z digest=sha256:64a2b572b8c3d47fe95159dcd44b846297b77d603977625d72b5685a1ed9be20

Observation e3d32f0a-1096-46af-bd20-229b998d3fb6 · outbound

This paper cites Llm-based data synthesis and distillation for high-quality text-to-sql training,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Llm-based data synthesis and distillation for high-quality text-to-sql training,

Reference 50

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source=pdf_text observed=2026-08-02T18:39:38.265359Z digest=sha256:7dd7c5e71538315cf7cff52ba250bc4a5bb665cf750b2313210813860c22519e

Observation edb8f102-cb51-4a0e-a707-fdf10814e889 · outbound

This paper cites On efficient multilevel clustering via wasserstein distances,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data On efficient multilevel clustering via wasserstein distances,

Reference 51

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source=pdf_text observed=2026-08-02T18:39:38.389062Z digest=sha256:d9fa96b3baf5186b46624c392e4a905b5920fbb8197d1467f452bef20c010117

Observation a40b8eae-a486-4fa1-87e9-68715e6489b5 · outbound

This paper cites Probabilistic multilevel clustering via composite transportation distance.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Probabilistic multilevel clustering via composite transportation distance

Reference 52

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source=pdf_text observed=2026-08-02T18:39:38.500617Z digest=sha256:6045a6fd1b390d8faa357a599516b1737ee01421d7a28693d022f9c0464631af

Observation ca32dfa6-9f6c-4137-a3a7-19a6a5003156 · outbound

This paper cites Multilevel clustering via Wasserstein means,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Multilevel clustering via Wasserstein means,

Reference 53

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source=pdf_text observed=2026-08-02T18:39:38.628808Z digest=sha256:4baf03edf6d65a6c4b503653b38130eb45a20d2d9f3a6db339f3c1009b824950

Observation be4814e1-2d51-4d2e-bb90-42456b69fcf6 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data On First-Order Meta-Learning Algorithms

Reference 54

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source=pdf_text observed=2026-08-02T18:39:38.741630Z digest=sha256:558704b474c741c7dcffcf6a1759d826ed553f043b1946eceba1af185366017d

Observation 8b97b553-fb54-4c32-99f7-df8ff924d86c · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 55

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source=pdf_text observed=2026-08-02T18:39:38.866263Z digest=sha256:f32c60b91f2ec6004accfdf797fff3c6408909a4d6c06e2c876b49da91df252c

Observation c7970e95-45bc-4d88-9193-2d11e28351c6 · outbound

This paper cites Sciencebenchmark: A complex real-world bench- mark for evaluating natural language to sql systems,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Sciencebenchmark: A complex real-world bench- mark for evaluating natural language to sql systems,

Reference 56

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source=pdf_text observed=2026-08-02T18:39:39.041515Z digest=sha256:6999c43b38a71b99f8c232e5690c9000da91ebc64dae19e2be57b8f10049442f

Observation dd7e1ca1-746a-40e7-9706-067f814ff1f0 · outbound

This paper cites Ehrsql: A practical text-to-sql benchmark for electronic health records,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Ehrsql: A practical text-to-sql benchmark for electronic health records,

Reference 57

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source=pdf_text observed=2026-08-02T18:39:39.212724Z digest=sha256:3fa909e02abee03a36fa630d5916cefd905be835d3a44bf311bc07007cbb45aa

Observation 2f4076ad-b182-4b36-9aec-fabba04ff503 · outbound

This paper cites Gnnevaluator: Evaluating gnn performance on unseen graphs without labels,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Gnnevaluator: Evaluating gnn performance on unseen graphs without labels,

Reference 58

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source=pdf_text observed=2026-08-02T18:39:39.351031Z digest=sha256:c5aaa00d65ba9a0e864a67815f91dfe23b3fa59919925ee973baf016db396f74

Observation e7e41c0b-c141-4d9b-8ba1-f7d0dd35c866 · outbound

This paper cites Qwen3 Technical Report.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Qwen3 Technical Report

Reference 59

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source=pdf_text observed=2026-08-02T18:39:39.486993Z digest=sha256:44240cf034131f4260c48cb2b9ae0053dc91096edf8bebe47795eb6b1f9b5445

Observation c4b2a521-22dd-41e9-acbb-5c789ccf1fdf · outbound

This paper cites The Llama 3 Herd of Models.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data The Llama 3 Herd of Models

Reference 60

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source=pdf_text observed=2026-08-02T18:39:39.629407Z digest=sha256:25f490be4c149ec7865f7b8813b8d119918856b9294cf04acaffb1f39d9367b1

Observation 9cd006b4-5232-4fdf-8309-b19ca0c5761c · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 61

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source=pdf_text observed=2026-08-02T18:39:39.779694Z digest=sha256:c747113393c3412b5cca10b00e3209b4fc72371ee1994c1c45ad910f3ca8130f

Observation c7ec1c35-9416-417b-b4f0-8e3989709c86 · outbound

This paper cites XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL

Reference 62

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source=pdf_text observed=2026-08-02T18:39:39.910501Z digest=sha256:33b1dc0d7b393c5d765ed949b7d34b185dbb6b39921b98810425a31411e4b464

Observation 080feb71-0879-4012-8ea0-e2554a78c33c · outbound

This paper cites Mixtral of Experts.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Mixtral of Experts

Reference 63

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source=pdf_text observed=2026-08-02T18:39:40.015940Z digest=sha256:a5210093478b23cfa1317f1fd253ffb25694acb4b34acafe9b27ca9ac6fd5fde

Observation e38cf667-42c9-4733-b827-d74440dfdf21 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data StarCoder 2 and The Stack v2: The Next Generation

Reference 64

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source=pdf_text observed=2026-08-02T18:39:40.135720Z digest=sha256:aa97338c83c170bf06d4efbae5f181950a1e2f8ea76f02fa85a03756ae964c25

Observation bae73236-909d-4514-9723-c1ac006363fe · outbound

This paper cites Code Llama: Open Foundation Models for Code.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Code Llama: Open Foundation Models for Code

Reference 65

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source=pdf_text observed=2026-08-02T18:39:40.301809Z digest=sha256:b5003e620d13cb969d2d56ee2ab3490f5e73c231793989309635b8f4be5f0420

Observation 3dc6bec4-1961-4b05-a68c-95ab1a27c922 · outbound

This paper cites Phi-4 Technical Report.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Phi-4 Technical Report

Reference 66

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source=pdf_text observed=2026-08-02T18:39:40.396982Z digest=sha256:82c9b54ecd239bd7ad85e0cc95bd30b92b7050fd3a29ae6c6a2ed3d3aa6c2a45

Observation ec65b310-3481-4cda-9105-86f82b30e10e · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Yi: Open Foundation Models by 01.AI

Reference 67

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source=pdf_text observed=2026-08-02T18:39:40.460834Z digest=sha256:fd14f093dfc329f2a1f3a6f5b8de09b8c6722ed25f53a051610dd416a0cd0ffa

Observation d8a5dafb-ffb8-4204-8603-683f5278236a · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Gemma: Open Models Based on Gemini Research and Technology

Reference 68

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source=pdf_text observed=2026-08-02T18:39:40.550882Z digest=sha256:3ec367fb13705a049bb4e59c767968d64f752c4fe000257c18071c413b3b071a

Observation 8a1ffac9-03c3-4bcb-a9ef-a128db973ed6 · outbound

This paper cites InternLM2 Technical Report.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data InternLM2 Technical Report

Reference 69

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source=pdf_text observed=2026-08-02T18:39:40.626602Z digest=sha256:f23641c1517517ce188f9f55b36f6db62386ddc84088edc18a5a3a24bc9c6a2d

Observation d8badaba-c093-444d-9291-198d138c5417 · outbound

This paper cites Athena: An ontology-driven system for natural language querying over relational data stores,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Athena: An ontology-driven system for natural language querying over relational data stores,

Reference 70

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source=pdf_text observed=2026-08-02T18:39:40.743753Z digest=sha256:b3b141704499d8c7d3bc00561ba9acdd8f3ee1c8cbe812a2b05c35ebaa1213a5

Observation 918ba1f7-c3c9-4242-85c7-3578a0f9d692 · outbound

This paper cites Athena++: Natural language querying for complex nested SQL queries,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Athena++: Natural language querying for complex nested SQL queries,

Reference 71

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source=pdf_text observed=2026-08-02T18:39:40.829518Z digest=sha256:852ac262cc8fcb2d9383c0e9c158d83fa98dd823b607ee11e05a66d620bf545a

Observation 8818f91e-d9f4-4ce9-a2a7-2dc1db62b9b0 · outbound

This paper cites Sqlizer: Query synthesis from natural language,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Sqlizer: Query synthesis from natural language,

Reference 72

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source=pdf_text observed=2026-08-02T18:39:40.986312Z digest=sha256:18bb9765bdd73f9b78bb95141d604813646abdcebcacd3ddb6f58b8af9da50f2

Observation bc813c4b-c735-4c9f-8ec4-b0729db6adcb · outbound

This paper cites Don’t judge a language model by its last layer: Contrastive learning with layer-wise attention pooling,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data Don’t judge a language model by its last layer: Contrastive learning with layer-wise attention pooling,

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source=pdf_text observed=2026-08-02T18:39:41.181757Z digest=sha256:294caa56c748b8200608f63d64fb17d9dae29f36a5f6a70b72c7f1a7f0ff6b72

Observation ad370d68-563f-4864-8248-cc0de690fa17 · outbound

This paper cites SimCSE: Simple contrastive learning of sentence embeddings,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data SimCSE: Simple contrastive learning of sentence embeddings,

Reference 74

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 70f0140f-6c74-49d6-b7df-ab574caa9630 · outbound

This paper cites PromptBERT: Improving BERT sentence embeddings with prompts,.

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data PromptBERT: Improving BERT sentence embeddings with prompts,

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-02T18:39:41.316604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation 0ea25dba-179d-4405-a524-fadfde9fb543 · inbound

Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning cites this paper.

Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-07-28T02:22:28.563646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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