Paper Citation Record · LEDGER

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing

As of 19 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 2 inbound Pith citation observations for arXiv:2506.21575.

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

pith.paper-citation-record.v1
2506.21575 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:10:59.678258Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:39:47.848753Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:58:32.442271Z

Reference resolution

54 of 54 outbound references displayed

verified exact1
verified fuzzy23
unresolved29
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62d56107-b541-423a-9fc3-4bc2b5ca2c41 · outbound

This paper cites The mighty torr: A benchmark for table reasoning and robustness.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing The mighty torr: A benchmark for table reasoning and robustness

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.436134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e68febd-3032-412c-9a3a-36ea5f356c44 · outbound

This paper cites A scalable llm framework for thera- peutic biomarker discovery: Grounding q/a generation in knowledge graphs and literature.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing A scalable llm framework for thera- peutic biomarker discovery: Grounding q/a generation in knowledge graphs and literature

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.746997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b90c0c1e-05a8-4286-a3fe-8006aedec611 · outbound

This paper cites Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.448037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 585e15a2-7cb5-46ff-87b1-10f2081f366f · outbound

This paper cites Combining human and machine intelligence for clinical trial eligibility querying.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Combining human and machine intelligence for clinical trial eligibility querying

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.736067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3dfd3213-b661-4f4a-b926-b9e612e76b65 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.457512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72834154-bac0-4788-b3da-82d1f7bc1ee4 · outbound

This paper cites GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.462433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 850b8d05-20cd-4f6d-baac-4c7db087b3ff · outbound

This paper cites CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.467266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0dd64a0-4e87-4ee5-a7fc-98c1e6db5ebb · outbound

This paper cites Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.471292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08fdda45-b62e-44c0-815c-1196ddfbf5cd · outbound

This paper cites The atis spoken language systems pilot corpus.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing The atis spoken language systems pilot corpus

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.723729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 562b501c-2907-4676-8a2f-a2660f4c55f8 · outbound

This paper cites Data-centric text-to-SQL with large language models.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Data-centric text-to-SQL with large language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.712211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0d7d1e0a-a8f4-45ac-a7a5-3803457a7279 · outbound

This paper cites OpenAI o1 System Card.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing OpenAI o1 System Card

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.481353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66d383c7-57ae-481b-ac84-bd85f0ec9aea · outbound

This paper cites StructGPT: A General Framework for Large Language Model to Reason over Structured Data.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing StructGPT: A General Framework for Large Language Model to Reason over Structured Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.485298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b85614b0-2687-4d0a-8e0c-857ba5db1295 · outbound

This paper cites Mimic-iii, a freely accessible critical care database.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Mimic-iii, a freely accessible critical care database

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.700843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 77c7d2f9-0085-454b-b027-da3c075a06b0 · outbound

This paper cites A survey on deep learning approaches for text-to-sql.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing A survey on deep learning approaches for text-to-sql

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.688278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d5f8feb6-6ed6-4f07-a018-b5917f218f25 · outbound

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

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Ehrsql: A practical text-to-sql benchmark for electronic health records

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.676863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9e618b9b-4e02-4771-a872-759b36d77bd8 · outbound

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

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Can llm already serve as a database interface? a big bench for large-scale database grounded text-to- sqls

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.664196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37c1c5a9-6c8d-4fd0-87c5-9131081a947e · outbound

This paper cites Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.506648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52b93251-4052-414a-8aa1-3620a0ddeb68 · outbound

This paper cites Bridging the gap: Enabling natural lan- guage queries for nosql databases through text-to-nosql translation.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Bridging the gap: Enabling natural lan- guage queries for nosql databases through text-to-nosql translation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.511713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d903bcc7-02d6-4b50-90da-a2596594e650 · outbound

This paper cites Sql-r1: Training natural language to sql reasoning model by reinforcement learning.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Sql-r1: Training natural language to sql reasoning model by reinforcement learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.516846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b00cd1d-91a8-42a5-b115-49e7d4679b85 · outbound

This paper cites Fine-tuning text-to-sql models with reinforcement-learning training objectives.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Fine-tuning text-to-sql models with reinforcement-learning training objectives

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.651103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7d48e553-acb5-4fcf-b2de-0766bd1003c7 · outbound

This paper cites Enhancing Text2Cypher with Schema Filtering.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Enhancing Text2Cypher with Schema Filtering

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.528667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a3547a4-b624-4301-8f17-79091d31587b · outbound

This paper cites Text2Cypher: Data Pruning using Hard Example Selection.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Text2Cypher: Data Pruning using Hard Example Selection

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:11:00.018068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fda3e9e1-185a-4656-b148-0f8ff04205b8 · outbound

This paper cites Text2Cypher: Bridging Natural Language and Graph Databases.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Text2Cypher: Bridging Natural Language and Graph Databases

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.537229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e1cd37b-0bd5-4ed0-ae30-1683c8662d9c · outbound

This paper cites Din-sql: Decomposed in- context learning of text-to-sql with self-correction.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Din-sql: Decomposed in- context learning of text-to-sql with self-correction

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.637088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1404987-59a5-431c-a904-0f3f53717fdf · outbound

This paper cites Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.548168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9565ff70-c30b-4bbe-ac61-b37e33956f92 · outbound

This paper cites SmBoP: Semi-autoregressive bottom-up semantic parsing.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing SmBoP: Semi-autoregressive bottom-up semantic parsing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.623706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad5b392c-35e5-44ed-b058-3ff186e7ccf5 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.558097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7784f1b4-5aec-4fdd-8a3d-9da11b2182f5 · outbound

This paper cites On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.563426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 080ff72e-d0d0-4b0d-80a4-6e611d757851 · outbound

This paper cites SM3-text-to-query: Synthetic multi- model medical text-to-query benchmark.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing SM3-text-to-query: Synthetic multi- model medical text-to-query benchmark

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.612305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 335bd416-cae7-4620-8044-e41787e7b9d2 · outbound

This paper cites Sparks of Tabular Reasoning via Text2SQL Reinforcement Learning.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Sparks of Tabular Reasoning via Text2SQL Reinforcement Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.575505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cdc9e21-0361-4829-9602-c75d4f4d1aff · outbound

This paper cites Query, don’t train: Privacy-preserving tabular prediction from ehr data via sql queries.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Query, don’t train: Privacy-preserving tabular prediction from ehr data via sql queries

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.579670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 295c4264-b86f-4e99-aa9c-a1eafe453ef2 · outbound

This paper cites TAP4LLM: Table provider on sampling, augmenting, and packing semi-structured data for large language model reasoning.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing TAP4LLM: Table provider on sampling, augmenting, and packing semi-structured data for large language model reasoning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.597953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 78492272-cbed-46f4-a5ed-d5eeb6843450 · outbound

This paper cites Auto-cypher: Improving llms on cypher generation via llm-supervised generation-verification framework.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Auto-cypher: Improving llms on cypher generation via llm-supervised generation-verification framework

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.584970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e28086b-c331-4813-aa07-3ea66bb31930 · outbound

This paper cites Natural Language Models for Data Visualization Utilizing nvBench Dataset.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Natural Language Models for Data Visualization Utilizing nvBench Dataset

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.591976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f6950c8-1f66-48f9-b579-c962a81a8b2f · outbound

This paper cites Chain-of-thought prompting elic- its reasoning in large language models.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Chain-of-thought prompting elic- its reasoning in large language models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.570927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2f7c7cfb-7ab8-4034-998a-c35f6360b79d · outbound

This paper cites Tablebench: A comprehensive and complex benchmark for table question answering.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Tablebench: A comprehensive and complex benchmark for table question answering

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.554072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 17c8551f-7760-46e6-9998-2f5c7bcbae59 · outbound

This paper cites Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.534319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d82a2682-4f1e-4814-970a-5e32429e0f8c · outbound

This paper cites DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.613345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c9ab5d5-5c5c-42a6-8780-dd6bf768c1b3 · outbound

This paper cites Fine-tuned LLMs know more, hallucinate less with few-shot sequence-to-sequence semantic parsing over Wikidata.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Fine-tuned LLMs know more, hallucinate less with few-shot sequence-to-sequence semantic parsing over Wikidata

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.506172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2d856597-09fc-44b9-a8fa-38c296fb38fe · outbound

This paper cites Qwen2.5 Technical Report.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Qwen2.5 Technical Report

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.623293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5edc6ba-352d-4acb-8a61-943a0c69ba07 · outbound

This paper cites Synthesizing text-to-SQL data from weak and strong LLMs.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Synthesizing text-to-SQL data from weak and strong LLMs

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.493079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f1a5447-09ac-468e-ae44-856ba5fe505c · outbound

This paper cites Neural machine translating from natural language to sparql.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Neural machine translating from natural language to sparql

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.479688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32c6590b-e746-417f-b342-ab629480ea6a · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.635171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6004cf02-27cd-4847-8051-fe284f2efb78 · outbound

This paper cites Knowgpt: Knowledge graph based prompting for large language models.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Knowgpt: Knowledge graph based prompting for large language models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.461510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 00ef39cb-9a9e-4f70-be64-8f6bbdc9388d · outbound

This paper cites Crt-qa: A dataset of complex reasoning question answering over tabular data.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Crt-qa: A dataset of complex reasoning question answering over tabular data

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.445095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3cd51436-3920-4350-92cc-fc3f2eb9c0e9 · outbound

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

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.647092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f7b01e0-c839-40ed-8672-f8e22aef947b · outbound

This paper cites SyntheT2C: Generating synthetic data for fine-tuning large language models on the Text2Cypher task.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing SyntheT2C: Generating synthetic data for fine-tuning large language models on the Text2Cypher task

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:11:00.433723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1b1e47b3-884c-4774-a3ac-71bf8d9a04e3 · outbound

This paper cites ‘sql” and.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing ‘sql” and

Reference 48

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T20:11:00.419345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 85f799d2-ddf7-4574-82d4-5fbc03cd6e02 · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:11:00.406469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6a6da09e-78bb-46d6-920f-2f9cf4303379 · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:11:00.393450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f23b2732-9bd9-421b-be05-75a795c2d284 · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:11:00.379524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 082a5e0a-7e0f-4ca0-a107-381ff12253ca · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:11:00.365432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 53ff3b0b-3df8-4ae1-b950-4b2650a93e14 · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:11:00.352833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 558f7c4e-42a8-4908-8335-1464641e7e24 · outbound

This paper cites an unresolved cited work.

STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing Unresolved cited work

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T20:10:59.608153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 1f741d50-c5cd-45b3-a0b3-bbd0a45ce8e2 · inbound

Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning cites this paper.

Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T11:39:47.848753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44297b82-0f01-4158-85cc-a8aaa80056be · inbound

Object Aligner: A Configurable JSON Schema Similarity Score for Graphs, Applied to LLM Prompt Optimization cites this paper.

Object Aligner: A Configurable JSON Schema Similarity Score for Graphs, Applied to LLM Prompt Optimization STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:32.443694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.