Paper Citation Record · LEDGER

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation

As of 22 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2507.06013.

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

pith.paper-citation-record.v1
2507.06013 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:18:40.429180Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T00:02:24.352947Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T00:02:25.416050Z

Reference resolution

50 of 50 outbound references displayed

verified exact4
verified fuzzy10
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9f86cdd-e171-4991-92e6-349b38c0cda7 · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Chain-of-thought prompting elicits reasoning in large language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:45.422300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0ba3fccc-2226-4fe9-ae22-657382821ca9 · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:35.137524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53f9b9af-a52e-44af-a0ec-2ac488ba2ab8 · outbound

This paper cites A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:35.220308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82ce68b3-7255-4f02-bcd9-b1713738dc80 · outbound

This paper cites Towards complex text-to-sql in cross-domain database with intermediate representation.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Towards complex text-to-sql in cross-domain database with intermediate representation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:45.196257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fb4c901d-7f53-48e3-9184-7315b0061afb · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:35.407575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92fdecae-8a3f-4778-b416-77b101fc9c97 · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:35.547480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 610254a7-1ca7-49d8-aa37-5c0f712709e8 · outbound

This paper cites an unresolved cited work.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Unresolved cited work

Reference 7

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:18:42.748565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9d1ebf35-2e02-48ff-8864-d7d589a31f3f · outbound

This paper cites Seq2sql: Generating structured queries from natural language using reinforcement learning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Seq2sql: Generating structured queries from natural language using reinforcement learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:44.974419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 42a16e87-6181-49c3-8c86-33a901f7e2e1 · outbound

This paper cites Vector valued polynomials, exponential polynomials and vector valued harmonic analysis.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Vector valued polynomials, exponential polynomials and vector valued harmonic analysis

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:18:42.499155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8a7b0064-fce6-4771-bbb8-5320ee5cfde0 · outbound

This paper cites Androutsopoulos, G.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Androutsopoulos, G

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:44.786612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ff86ec9e-4122-4854-a842-121c5715353c · outbound

This paper cites Text-to-sql empowered by large language models: A benchmark evaluation.arXiv preprint arXiv:2308.00000, 2023.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Text-to-sql empowered by large language models: A benchmark evaluation.arXiv preprint arXiv:2308.00000, 2023

Reference 11

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:18:42.242000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0b6c5a23-72f9-424f-82df-3f58b59f3d14 · outbound

This paper cites UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:18:41.991745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d10165b5-76eb-492f-8b39-a3af191bad48 · outbound

This paper cites Learning to think: Information-theoretic reinforcement fine-tuning for efficient reasoning.arXiv preprint arXiv:2505.10425, 2025.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Learning to think: Information-theoretic reinforcement fine-tuning for efficient reasoning.arXiv preprint arXiv:2505.10425, 2025

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.315208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd11cafb-5c0d-4a8f-907e-0bb872252e73 · outbound

This paper cites Group Relative Policy Optimization for Image Captioning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Group Relative Policy Optimization for Image Captioning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.415994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14868fc8-a918-4bf0-a8a4-9d9464a4753a · outbound

This paper cites Hao et al.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Hao et al

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.501873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65b7558d-6e21-4157-a9f1-ddb5a96089ed · outbound

This paper cites REARANK: Reasoning Re-ranking Agent via Reinforcement Learning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation REARANK: Reasoning Re-ranking Agent via Reinforcement Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.607918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b75e31b2-4947-4576-8036-acb5dc379616 · outbound

This paper cites SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.773869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecdf1f71-6926-44db-a58e-851be3208b92 · outbound

This paper cites ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:36.890036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50959ac0-77d8-4e38-b7ff-b5deabcf2805 · outbound

This paper cites Defining and characterizing reward gaming.Advances in Neural Information Processing Systems, 35:9460–9471, 2022.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Defining and characterizing reward gaming.Advances in Neural Information Processing Systems, 35:9460–9471, 2022

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:37.032528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 872b9a67-5e1e-4cbe-a566-e602c5de6ded · outbound

This paper cites an unresolved cited work.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:18:44.505404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be9160db-0e64-42b9-bfcb-fc0c362d3ce2 · outbound

This paper cites Rat-sql: Relation-aware schema encoding and linking for text-to-sql parsers.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Rat-sql: Relation-aware schema encoding and linking for text-to-sql parsers

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:44.229039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c0398d13-79a2-4faa-855f-7e7e34fa247b · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:37.337497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99209bd4-50e2-4dd5-83e8-4c7e95064fe1 · outbound

This paper cites Semantic decomposition of question and sql for text-to-sql parsing.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Semantic decomposition of question and sql for text-to-sql parsing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:43.894382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b5c3e63d-49cf-41d0-849a-c65f7910154b · outbound

This paper cites Multi-reward text-to-sql: Aggregating execution, syntax, and schema feedback.arXiv preprint arXiv:2501.23456, 2025.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Multi-reward text-to-sql: Aggregating execution, syntax, and schema feedback.arXiv preprint arXiv:2501.23456, 2025

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:18:41.446593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ad8e2f6-fd69-4eb3-8507-7673b3cc1993 · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:43.703261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83504291-2a3c-4acd-9aee-dc3976797684 · outbound

This paper cites Synthetic-text-to-sql: A synthetic dataset for training language models to generate sql queries from natural language prompts.arXiv preprint arXiv:2404.00000, 2024.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Synthetic-text-to-sql: A synthetic dataset for training language models to generate sql queries from natural language prompts.arXiv preprint arXiv:2404.00000, 2024

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:37.857092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71875f5d-3fd6-4824-8a2c-ca4c4ca9f9d9 · outbound

This paper cites Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.Advances in Neural Information Processing Systems, 36, 2024.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.Advances in Neural Information Processing Systems, 36, 2024

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.069089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4036164-5035-4f94-ab42-9af7a20fcaf2 · outbound

This paper cites Qwen2.5-Coder Technical Report.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Qwen2.5-Coder Technical Report

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.166180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d978c357-d912-4761-8ffd-c9bff06b1690 · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.234160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99a8bbd8-1b77-4cc0-8bdb-ec5d138784dc · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.298531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de11fb03-cdfd-4ade-bc52-3a32afa56573 · outbound

This paper cites Proximal Policy Optimization Algorithms.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Proximal Policy Optimization Algorithms

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.403564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f2ed0ca-661f-4bca-bb51-fc5f59350257 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Efficient memory management for large language model serving with pagedattention

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.504256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e1728a6-ab02-44a2-8312-3188f63d4b44 · outbound

This paper cites SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.635881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a1c392c-5e2c-4a08-a44c-b3dcb06b6e52 · outbound

This paper cites Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.761833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f740ef8-4199-44ff-b6b5-65cab1090ed3 · outbound

This paper cites Stabilizing llm training: Techniques and insights.arXiv preprint arXiv:2501.00000, 2025.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Stabilizing llm training: Techniques and insights.arXiv preprint arXiv:2501.00000, 2025

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.811655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89f4ffce-cc76-433c-b930-53cc467e322c · outbound

This paper cites Granite Code Models: A Family of Open Foundation Models for Code Intelligence.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Granite Code Models: A Family of Open Foundation Models for Code Intelligence

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:38.885619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09194789-4121-42ba-9971-e94621ab0f63 · outbound

This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.026990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfacdf5d-0e31-4e9a-bad4-4d3e472f92fc · outbound

This paper cites The Llama 3 Herd of Models.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation The Llama 3 Herd of Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.125846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b257213-dd21-4bd6-a571-593d29b5e95c · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.230792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 986c1ec0-2bfa-45e4-ad35-b2f11c4f728c · outbound

This paper cites Qwen2.5 Technical Report.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Qwen2.5 Technical Report

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.314273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9a90797-c9d6-490d-beda-91f3b891d4e7 · outbound

This paper cites Think2sql: Reinforce llm reasoning capabilities for text2sql.arXiv preprint arXiv:2504.00000, 2025.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Think2sql: Reinforce llm reasoning capabilities for text2sql.arXiv preprint arXiv:2504.00000, 2025

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.365851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e587765-b981-44ff-a82b-9db29926d4f2 · outbound

This paper cites Sft codes: A lightweight supervised approach for sql generation.Proceedings of SIGMOD 2024, 2024.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Sft codes: A lightweight supervised approach for sql generation.Proceedings of SIGMOD 2024, 2024

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:43.375335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3dc3f8f2-caf2-4449-b3eb-334796d5ea1b · outbound

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

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation StarCoder 2 and The Stack v2: The Next Generation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.589559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a1ab5dd-2398-42bd-8f3d-ba3959c4bbcf · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:39.703645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e910cc6f-e673-45c3-852b-95538a7094de · outbound

This paper cites Codestral: Mistral ai’s first code generation model, 2024.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Codestral: Mistral ai’s first code generation model, 2024

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:43.112025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c24e1922-b3ce-4ee5-87c3-89c49db16885 · outbound

This paper cites Codes: Towards building open-source language models for text-to-sql.Proceedings of the ACM on Management of Data, 2024.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Codes: Towards building open-source language models for text-to-sql.Proceedings of the ACM on Management of Data, 2024

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:18:42.980247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7066eb41-bfa0-47bb-aa42-a217c22688a1 · outbound

This paper cites Mixtral of Experts.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Mixtral of Experts

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:40.022630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff3db592-2037-443d-aa73-e85a8ae6cb59 · outbound

This paper cites The Dawn of Natural Language to SQL: Are We Fully Ready?.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation The Dawn of Natural Language to SQL: Are We Fully Ready?

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:40.154537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe1636fe-aa28-4d0a-a15d-841dcc051593 · outbound

This paper cites A General Theoretical Paradigm to Understand Learning from Human Preferences.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation A General Theoretical Paradigm to Understand Learning from Human Preferences

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:40.283348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e78474da-27e2-42ad-b862-1e7208a9e88f · outbound

This paper cites Concrete Problems in AI Safety.

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation Concrete Problems in AI Safety

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T19:18:40.429180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 1f1aafee-1b54-4083-bc9a-3ec23cdd6fa6 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation

Reference 151

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:25.418462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.