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Paper Citation Record · LEDGER

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2509.07159.

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

pith.paper-citation-record.v1
2509.07159 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:48:35.507042Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T22:27:38.131329Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:37:09.689700Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact1
  • verified fuzzy11
  • unresolved35
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7dba392b-cd12-45ea-9f5a-6d502b233d0b · outbound

This paper cites RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

Reference 1

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source=pdf_text observed=2026-08-04T22:48:29.563152Z digest=sha256:ecbe8deba9bd44d56d33242dede558567a2e567d5ed04d35bffc40533e22e633

Observation fbdd959a-5eb6-4218-b1c0-167ad7b6e410 · outbound

This paper cites PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models

Reference 2

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source=pdf_text observed=2026-08-04T22:48:29.725357Z digest=sha256:57a3c937d5360553718f4f138359f6fcae0eb64e02a8b96b02b9f32e97fedec2

Observation 6f3ccdbf-92f9-4f70-9d17-dc49e5e0af4d · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Din-sql: Decomposed in-context learning of text-to-sql with self-correction,

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:29.866560Z digest=sha256:90771c17720f8b6a20d9de87db4e447c25e5fb063f924a9a3d3b93adee56ca76

Observation 6011d5b3-1b1d-4021-a4da-e654f436a32d · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 4

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source=pdf_text observed=2026-08-04T22:48:29.957519Z digest=sha256:acdba541333120d33e4dbd13b480e4d95e0d57a57526ab4cc5201a9062cc8148

Observation ad15bfe4-7f61-40ac-85d2-b9fa4f0990d9 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 5

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source=pdf_text observed=2026-08-04T22:48:30.050130Z digest=sha256:cdf004d785359da4c7b530064929a28e3e96a6f770cb13176c1a3e9ca8d89069

Observation 6517d93b-7746-4627-9adb-70b92cbe20da · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:30.156913Z digest=sha256:6b3482cb79faf9486f4ca1d7fe1cc1045e307c901b9fcaf69e2ae03cbbcb97cc

Observation 7c6e00aa-4f3f-4dd9-8a7a-c153c1e49ae4 · outbound

This paper cites CRUSH4SQL: Collective retrieval using schema hallucination for Text2SQL,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning CRUSH4SQL: Collective retrieval using schema hallucination for Text2SQL,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:30.319501Z digest=sha256:db3fba74e44ce016b83b91d425d8e891d11b2ead6e6c41d90f385f1069fa11a0

Observation 1a7cc7e8-0b81-4b0f-8f1c-a71f4b72cc25 · outbound

This paper cites Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Reference 9

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source=pdf_text observed=2026-08-04T22:48:30.458664Z digest=sha256:a54df59de784ec5c424bc966972c40f67cf5958ba4648b90aa8643a5cd0dac9c

Observation 74a2f3c1-c7d1-4bc6-9fac-003778be3ee0 · outbound

This paper cites Fundamental Challenges in Evaluating Text2SQL Solutions and Detecting Their Limitations.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Fundamental Challenges in Evaluating Text2SQL Solutions and Detecting Their Limitations

Reference 10

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source=pdf_text observed=2026-08-04T22:48:30.522136Z digest=sha256:29890da156ceac573236c43292260ca171e42c48ffac0939fec8153f7f3fa7cb

Observation a9e81ea7-dec7-4a42-a4de-223c3c59949f · outbound

This paper cites OpenAI o1 System Card.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning OpenAI o1 System Card

Reference 11

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source=pdf_text observed=2026-08-04T22:48:30.668066Z digest=sha256:e74ee80cefc9e0aa966ccc6790614825aa8415dc20d89749045897851a879e4c

Observation b3a70ecb-f05b-4523-9a60-1c7f15eb6aef · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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source=pdf_text observed=2026-08-04T22:48:30.814866Z digest=sha256:4902fee4989c7bd96847ffd0c0d83e947630907e7271302b1dc30b9749771471

Observation ce2ee7c7-16b6-4122-bc1b-b76a70beea50 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 13

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source=pdf_text observed=2026-08-04T22:48:30.994236Z digest=sha256:91cbf039b935b4f40a6bdf9861a25caa2f09b51b5082a2869065545c0b970551

Observation 97c8592b-73ef-40a1-88a0-ac14bc90f84a · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 14

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source=pdf_text observed=2026-08-04T22:48:31.148255Z digest=sha256:c23ecf7b55c01f325a06b9174af7a740e35b42c51d8a003853c3c74747ef3185

Observation 27ae32ed-2e65-414f-8bbb-07b242acc41b · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 15

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source=pdf_text observed=2026-08-04T22:48:31.257641Z digest=sha256:a15955cdf25caa4d15978395a2d98b5ed69477b3d0ef8a9271b34eb6fac1170d

Observation 75c99ca4-73b6-494b-b253-a4bd46b2ea98 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 16

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source=pdf_text observed=2026-08-04T22:48:31.367398Z digest=sha256:226dfcd75c68d841dd3e9d49fa2d0ff6a1e46e393c3601e4559ae7fec1bdf388

Observation 2f0b690f-9baf-4777-a627-dce295f3bf87 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Resdsql: Decoupling schema linking and skeleton parsing for text-to-sql,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:31.470911Z digest=sha256:3ba702fac4eba9e884235bb62dd6d124ffcf26fd14b0bc6d7611022389bf4812

Observation 55b487a0-5d88-4fa7-ba0d-9c5646571899 · outbound

This paper cites Codes: Towards building open-source language models for text-to-sql,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Codes: Towards building open-source language models for text-to-sql,

Reference 18

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:31.636496Z digest=sha256:cafec6c9c8522bfe16788d2b226b24bfc640dd2306e754b54f1dcc3e02369295

Observation 1042834e-3efa-4adb-b22e-474f519d7ff2 · outbound

This paper cites PSM-SQL: Progressive Schema Learning with Multi-granularity Semantics for Text-to-SQL.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning PSM-SQL: Progressive Schema Learning with Multi-granularity Semantics for Text-to-SQL

Reference 19

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local_arxiv, observed 2026-08-04T22:48:35.858315Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:31.915171Z digest=sha256:d53284207da82d868f3ff1189d9a8a55022a41deb26f05d629aa2775ebf27246

Observation f54fae96-d2e7-45e5-b0aa-7fa7a3132c62 · outbound

This paper cites ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought

Reference 20

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source=pdf_text observed=2026-08-04T22:48:32.097902Z digest=sha256:ac9a408474afda0e637d2aaa892a2a898bec6852ccfff244bb2ebc0d0a8c0d05

Observation f8831616-8af3-49c1-b0bd-b9217d996811 · outbound

This paper cites CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

Reference 21

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source=pdf_text observed=2026-08-04T22:48:32.217291Z digest=sha256:aaf6bcc594c8ebf10ddd7e7277e1ea8eb7cfb2f576cb6f947d9ffbda0322111e

Observation 45075c7d-bb99-4c13-8679-ede3bb55d1c1 · outbound

This paper cites Re- flexion: Language agents with verbal reinforcement learning,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Re- flexion: Language agents with verbal reinforcement learning,

Reference 22

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source=pdf_text observed=2026-08-04T22:48:32.315334Z digest=sha256:2627970df1479328c83d71434ed83e0bbaaba77717bd4a2cfb922a217bdbf830

Observation 0b83e491-fa31-4137-a95e-543a0112594d · outbound

This paper cites Text-to-SQL Calibration: No Need to Ask -- Just Rescale Model Probabilities.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Text-to-SQL Calibration: No Need to Ask -- Just Rescale Model Probabilities

Reference 23

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source=pdf_text observed=2026-08-04T22:48:32.435301Z digest=sha256:9c722f83573210f5f7d4a59b81851fece974e21493d42a0353913c87fa099aa6

Observation 0e6f288c-3cec-4927-bf7e-43380ab7134b · outbound

This paper cites Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback

Reference 24

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source=pdf_text observed=2026-08-04T22:48:32.557614Z digest=sha256:a652029786d78801e6cacf7369f9e77a8fad8bd31240b620fe5630e0cbe5544d

Observation 77c19d91-9dd0-49e4-bf54-bcd3b4dcf963 · outbound

This paper cites AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning

Reference 25

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source=pdf_text observed=2026-08-04T22:48:32.672774Z digest=sha256:c6d37fb2975e720a70051d836c40724bfbdaa884509815f79e777af339bc324c

Observation 4f0045ce-3163-43a5-b572-3aa99722327f · outbound

This paper cites Qwen3 Technical Report.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Qwen3 Technical Report

Reference 26

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source=pdf_text observed=2026-08-04T22:48:32.741532Z digest=sha256:dee9b091b9e7d6a4a07c1b715459138e8c844f4a72922fad07d78b4489eee041

Observation 98025b53-ca3d-4a8b-983b-95708b9b640b · outbound

This paper cites Phi-4-reasoning Technical Report.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Phi-4-reasoning Technical Report

Reference 27

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source=pdf_text observed=2026-08-04T22:48:32.864628Z digest=sha256:7ee9b85e4aca55273d3371a8bd98281cc0e73675387c50cc2821cba01a95a55c

Observation db449283-f2bf-4870-853d-5586e3b63f01 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 28

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source=pdf_text observed=2026-08-04T22:48:32.944371Z digest=sha256:7fef956ae8dac93dba1d43f35ca3626815d06d5bdd6b4d2165800a3df1baf81c

Observation cdf436d8-19d0-447d-b916-0d7c483b81c0 · outbound

This paper cites In-context reinforcement learn- ing with retrieval-augmented generation for text-to-sql,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning In-context reinforcement learn- ing with retrieval-augmented generation for text-to-sql,

Reference 29

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:33.077418Z digest=sha256:81d818000ef902dd28c20d2fbb75229a911d0a8eab21c41ebbef38f6389fc0a1

Observation d32f97e6-bbd0-4295-827b-7badb9ca3cb2 · outbound

This paper cites LLM-based SQL generation with reinforcement learning,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning LLM-based SQL generation with reinforcement learning,

Reference 30

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:33.212227Z digest=sha256:8d82027176037aaae4e9e441dd96c8692f582560e88449764c3b2c372639384f

Observation d4018a62-2874-45a5-8c83-c4e433212026 · outbound

This paper cites STaR-SQL: Self-Taught Reasoner for Text-to-SQL.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning STaR-SQL: Self-Taught Reasoner for Text-to-SQL

Reference 31

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source=pdf_text observed=2026-08-04T22:48:33.340134Z digest=sha256:c38a153c8037f43ba6193c0459d3ff0fc719580cc154f2ae5da62a0210f5cf8e

Observation 3e16180a-328b-4c85-ab63-22fa105c55ef · outbound

This paper cites Deepsql-r1: A quantized llm for high-performance and reinforcement driven nl2sql generation,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Deepsql-r1: A quantized llm for high-performance and reinforcement driven nl2sql generation,

Reference 32

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source=pdf_text observed=2026-08-04T22:48:33.452927Z digest=sha256:ef39f7bfa01881e5ca147d6f06b8c532fd7ea7156f5a3dbb7d3833e60840e972

Observation 9d2d5223-45f0-4358-884d-c55f0ecaa005 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL

Reference 33

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source=pdf_text observed=2026-08-04T22:48:33.600738Z digest=sha256:cc113998d9f5e21e5b3cc3691478da357afd5e3989a0eefdb167c887c4366d02

Observation 237fd520-82e5-4f2e-af83-900fcefea443 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Sql-r1: Training natural language to sql reasoning model by reinforcement learning,

Reference 34

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source=pdf_text observed=2026-08-04T22:48:33.751694Z digest=sha256:94d7e5212524ed43cc111c63913a6808270ccac9897765d80a041e67c60a5ffc

Observation 41fd099f-688c-49c1-b414-b11afec62ecf · outbound

This paper cites Arctic-Text2SQL-R1: Simple rewards, strong reasoning in Text-to-SQL,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Arctic-Text2SQL-R1: Simple rewards, strong reasoning in Text-to-SQL,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-04T22:48:37.005444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:33.872388Z digest=sha256:e6e4d7e35728b8ec35231b123d9cb0fc039e19f8d9793fda1b959a0491dfdc66

Observation bce16f20-6315-433b-9c78-4789c365ef49 · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning ReAct: Synergizing reasoning and acting in language models,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T22:48:36.762743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:34.018256Z digest=sha256:4d77e261502f079702ccdf9228237ec86296b9af1d3f19d94e59a2cae8358c76

Observation 7ee4200b-0f00-4883-a0b1-0b6bcba8266d · outbound

This paper cites Teaching Large Language Models to Self-Debug.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Teaching Large Language Models to Self-Debug

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:34.256066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:34.256066Z digest=sha256:1afa9f7faca46533bbe3587aca8cc4c06980224a67132d1a50c22cc202091c40

Observation b7004d49-9a8c-4f91-a0c8-f2b5c8d2aa92 · outbound

This paper cites Intercode: Standard- izing and benchmarking interactive coding with execution feedback,.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Intercode: Standard- izing and benchmarking interactive coding with execution feedback,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T22:48:36.503451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:34.425680Z digest=sha256:baca9b710745a47baf8e123751675003ce4d3f1854ddaa5bcb350bc038bbde7d

Observation b44ce5d9-939f-484e-bd8d-5dcdf34fe5ff · outbound

This paper cites CodeR: Issue Resolving with Multi-Agent and Task Graphs.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning CodeR: Issue Resolving with Multi-Agent and Task Graphs

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:34.602321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:34.602321Z digest=sha256:7b1d7b078542f08f16883424537469234000c0c678661409b5bf02c60c1cf66d

Observation 8fcf7fc0-78f6-4f8b-a49f-2a7619730df3 · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:34.743771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:34.743771Z digest=sha256:4ca5a4cf38da88daf89b31727f33fc41090ac9635ebd518794505f17bd80bec6

Observation 7752f5c2-5648-4001-b361-30d66e970498 · outbound

This paper cites Agentless: Demystifying LLM-based Software Engineering Agents.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Agentless: Demystifying LLM-based Software Engineering Agents

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:34.936810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:34.936810Z digest=sha256:b1fdef80532a03c205979169900fc8f32593986ab74f48d47576c243efb68964

Observation 8f863c8e-2276-43f6-ae06-9b604840570b · outbound

This paper cites ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Consensus Enforcement, and Column Exploration.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Consensus Enforcement, and Column Exploration

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.017017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.017017Z digest=sha256:ab830a947100a0992a75be567e10a5d2067665b32afb24cbf788b7df50061f7f

Observation efab0355-7913-4e39-941f-dcc5502ff3a8 · outbound

This paper cites Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.073263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.073263Z digest=sha256:f20c02f57ae382582b92eaf260e3b9e542c0aed8a65f30e40e81ba10035a7e8e

Observation 44088e0f-36b7-4a08-838c-cd43d73ae58e · outbound

This paper cites OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.137217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.137217Z digest=sha256:686b905f824997746e648e5ae82a22fd215e432fe75c7fc7b9fdf2fdf50e787a

Observation dcca5008-9b55-43de-9806-1721500ab18e · outbound

This paper cites Qwen2.5-Coder Technical Report.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Qwen2.5-Coder Technical Report

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.226847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.226847Z digest=sha256:d65454664d1ae1f6e6646319194cd4fcb7b36d702cfcebfa3ea9559353e6fec4

Observation d57bb88b-b0ba-4178-9545-b0c12dc9f7b9 · outbound

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

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T22:48:36.186615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-04T22:48:35.352397Z digest=sha256:a1eb09d456040de9bcdcef316b93f5691b3b3e3198f7c8360006f67d1bf568ed

Observation c93f3711-8b14-42d9-9fea-df62705ed78e · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning gpt-oss-120b & gpt-oss-20b Model Card

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.455714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.455714Z digest=sha256:f9fda73721515c59bddd27252ca0cfaa994584173e0d2e179162471ea9416677

Observation 34805e41-32a4-4693-9f53-819be52d2dd9 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning HybridFlow: A Flexible and Efficient RLHF Framework

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:35.507042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:35.507042Z digest=sha256:a5a94fcfa75a82bad2e8b009978bc1e110d086364cb515805d2e5446ffd0d572

Observation 57258685-a8c4-455e-bdf6-c822a23506aa · outbound

This paper cites Available: https://doi.org/10.1145/3654930.

PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning Available: https://doi.org/10.1145/3654930

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T22:48:31.755748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:48:31.755748Z digest=sha256:31e71b66c6a057b010260bfbfd317eeb8cdc4e2f29cc9d477767ba7a67b2c3b6

Pith citing papers

Observation 237f5cc8-f20e-454a-88fb-2948c19b4b3d · inbound

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards cites this paper.

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:37:09.691365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T22:27:38.131329Z digest=sha256:76f6d32417bc9fcef53cd73bd3af09e036b0f0d5f9144057340cc9841e7a55fb