Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T21:17:14.346359Z
Paper Citation Record · LEDGER
Neuro-Symbolic Data Generation for Math Reasoning
As of 17 August 2026, this Paper Citation Record lists 88 of 88 outbound references and 3 inbound Pith citation observations for arXiv:2412.04857.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:40:08.816339Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T23:00:47.702466Z
Reference resolution
88 of 88 outbound references displayed
- verified exact1
- verified fuzzy45
- unresolved41
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3b20633a-c25b-43c5-be32-5bdd77146394 · outbound
This paper cites Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, and Vedant Misra.
Neuro-Symbolic Data Generation for Math Reasoning Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, and Vedant Misra
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:12.794394Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4da938e-c257-433b-86d1-c85bf8324d7a · outbound
This paper cites an unresolved cited work.
Neuro-Symbolic Data Generation for Math Reasoning Unresolved cited work
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:12.822260Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f09e8c5-a7eb-4ce5-beaf-6a28f86e1c1d · outbound
This paper cites A Survey of Large Language Models.
Neuro-Symbolic Data Generation for Math Reasoning A Survey of Large Language Models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:12.864759Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28944a8b-4977-4ac4-b20b-6cada206b900 · outbound
This paper cites A Survey on Large Language Model based Autonomous Agents.
Neuro-Symbolic Data Generation for Math Reasoning A Survey on Large Language Model based Autonomous Agents
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:12.913133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2af9f3f3-468a-42dd-a2b7-09106c3492f3 · outbound
This paper cites Chatgpt for good? on opportunities and challenges of large language models for education.
Neuro-Symbolic Data Generation for Math Reasoning Chatgpt for good? on opportunities and challenges of large language models for education
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:12.964752Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a53f30c8-3749-4eb0-94e1-3a89236cd8ee · outbound
This paper cites A survey on evaluation of large language models.
Neuro-Symbolic Data Generation for Math Reasoning A survey on evaluation of large language models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.005662Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fb538c0-8acb-4313-b338-9188f7372ef6 · outbound
This paper cites SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models.
Neuro-Symbolic Data Generation for Math Reasoning SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.044874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c444e9b8-2e2d-45f6-a7d1-b51a7c786dcd · outbound
This paper cites An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP).
Neuro-Symbolic Data Generation for Math Reasoning An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP)
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T21:17:14.972563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 10e396b0-2f39-4d67-a49a-4e228e7af54b · outbound
This paper cites DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks.
Neuro-Symbolic Data Generation for Math Reasoning DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.124865Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd4d6c42-2119-481e-a0e2-1e12995f5832 · outbound
This paper cites Training Verifiers to Solve Math Word Problems.
Neuro-Symbolic Data Generation for Math Reasoning Training Verifiers to Solve Math Word Problems
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.157009Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fb4bbf4-a3bc-49f7-941c-ad742a235b39 · outbound
This paper cites Measuring mathematical problem solving with the math dataset.
Neuro-Symbolic Data Generation for Math Reasoning Measuring mathematical problem solving with the math dataset
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.163074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc288421-7ff5-404b-a4d8-8bbeb9e495c7 · outbound
This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.
Neuro-Symbolic Data Generation for Math Reasoning Are NLP Models really able to Solve Simple Math Word Problems?
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.170174Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a270e69-32f8-4b9f-8ba3-fa26be4cbc75 · outbound
This paper cites Llemma: An Open Language Model For Mathematics.
Neuro-Symbolic Data Generation for Math Reasoning Llemma: An Open Language Model For Mathematics
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.177653Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3fad672f-8b87-44cd-a5b8-f31ee085b08e · outbound
This paper cites Sampling constraint satisfaction solutions in the local lemma regime.
Neuro-Symbolic Data Generation for Math Reasoning Sampling constraint satisfaction solutions in the local lemma regime
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.186915Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee9680d0-9c0b-4dfe-9d5b-192ae4190d9d · outbound
This paper cites Softened symbol grounding for neuro-symbolic systems.
Neuro-Symbolic Data Generation for Math Reasoning Softened symbol grounding for neuro-symbolic systems
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.219024Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84a39f25-3c5b-4430-9629-2a4595d1e2d0 · outbound
This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.
Neuro-Symbolic Data Generation for Math Reasoning Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.229296Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62261583-4bd8-42e1-8390-d2c9a6fd356b · outbound
This paper cites Mistral 7B.
Neuro-Symbolic Data Generation for Math Reasoning Mistral 7B
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.246285Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a1b8704-31e0-48c1-9fdf-603319b1afc0 · outbound
This paper cites A diverse corpus for evaluating and developing english math word problem solvers.
Neuro-Symbolic Data Generation for Math Reasoning A diverse corpus for evaluating and developing english math word problem solvers
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.250510Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 419d693f-9eee-4cca-ba71-acf869273ad1 · outbound
This paper cites The SMT-LIB Standard: Version 2.6.
Neuro-Symbolic Data Generation for Math Reasoning The SMT-LIB Standard: Version 2.6
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.308611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2e68f830-4a29-4c24-8ee2-01cc1bf336d3 · outbound
This paper cites Z3: An efficient smt solver.
Neuro-Symbolic Data Generation for Math Reasoning Z3: An efficient smt solver
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.280936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fb8079e9-fbef-480f-bdfd-87d2f364b888 · outbound
This paper cites cvc5: A versatile and industrial-strength smt solver.
Neuro-Symbolic Data Generation for Math Reasoning cvc5: A versatile and industrial-strength smt solver
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.277850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d1071e2-af87-49ea-adf0-b5616797ef1e · outbound
This paper cites The mathsat 4 smt solver: Tool paper.
Neuro-Symbolic Data Generation for Math Reasoning The mathsat 4 smt solver: Tool paper
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.227017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ccc3a315-03a6-4de1-b9b0-535f60df6f7c · outbound
This paper cites Sympy: symbolic computing in python.
Neuro-Symbolic Data Generation for Math Reasoning Sympy: symbolic computing in python
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.169189Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 30ef39cd-b237-4be4-adf3-05380da55bd2 · outbound
This paper cites Scipy 1.0: fundamental algorithms for scientific computing in python.
Neuro-Symbolic Data Generation for Math Reasoning Scipy 1.0: fundamental algorithms for scientific computing in python
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.348581Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16fab5ee-7660-4ad2-992e-a9cd34a7b1ce · outbound
This paper cites The strategy challenge in smt solving.
Neuro-Symbolic Data Generation for Math Reasoning The strategy challenge in smt solving
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.101161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fb4e2768-5ad0-4fa1-b978-876369d42a18 · outbound
This paper cites The complexity of enumeration and reliability problems.
Neuro-Symbolic Data Generation for Math Reasoning The complexity of enumeration and reliability problems
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.068492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5dec9c2a-058b-4cc6-adb5-42d265ce90a2 · outbound
This paper cites The markov chain monte carlo method: an approach to approximate counting and integration.
Neuro-Symbolic Data Generation for Math Reasoning The markov chain monte carlo method: an approach to approximate counting and integration
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:17.023955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c030ba39-cb5c-40ab-bf92-4f3bca9d859c · outbound
This paper cites Uniform solution sampling using a constraint solver as an oracle.
Neuro-Symbolic Data Generation for Math Reasoning Uniform solution sampling using a constraint solver as an oracle
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.993381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 923055ce-3701-4e71-a65d-e8b3aa6165b6 · outbound
This paper cites Autoformalization with large language models.
Neuro-Symbolic Data Generation for Math Reasoning Autoformalization with large language models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.531035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d130101-4012-4b6a-a3b7-9a435979810e · outbound
This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.
Neuro-Symbolic Data Generation for Math Reasoning WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.555980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a0ea67d-8a24-4384-acaf-28410a04ab85 · outbound
This paper cites MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning.
Neuro-Symbolic Data Generation for Math Reasoning MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.576806Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74a27026-1c1d-4fce-bb0e-f6d79b5a6530 · outbound
This paper cites MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning.
Neuro-Symbolic Data Generation for Math Reasoning MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.627074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b2e21c0-25fd-47cc-b516-eab03315c8ea · outbound
This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.
Neuro-Symbolic Data Generation for Math Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.634393Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4fcb33f-178b-43da-9b23-2462b86f1680 · outbound
This paper cites Solving quantitative reasoning problems with language models.
Neuro-Symbolic Data Generation for Math Reasoning Solving quantitative reasoning problems with language models
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.664732Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80987479-9e09-4406-9f8b-3e66d6b4c9ae · outbound
This paper cites Bleu: a method for automatic evaluation of machine translation.
Neuro-Symbolic Data Generation for Math Reasoning Bleu: a method for automatic evaluation of machine translation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.684810Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1aea841a-4d0b-4f2b-a661-3fde24562110 · outbound
This paper cites Testing language models on a held-out high school national finals exam.
Neuro-Symbolic Data Generation for Math Reasoning Testing language models on a held-out high school national finals exam
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.714737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e989fa3-409d-462d-8d28-10b067e07e0e · outbound
This paper cites Large language models for mathematical reasoning: Progresses and challenges.
Neuro-Symbolic Data Generation for Math Reasoning Large language models for mathematical reasoning: Progresses and challenges
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.924886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 45f51399-df82-4163-9a4f-c631a155ee5a · outbound
This paper cites A survey of deep learning for mathematical reasoning.
Neuro-Symbolic Data Generation for Math Reasoning A survey of deep learning for mathematical reasoning
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.902967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation adfbb97f-3492-42f1-8a54-fd38e3d86d2e · outbound
This paper cites Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts.
Neuro-Symbolic Data Generation for Math Reasoning Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.885894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6ffcc79e-104a-4e90-b406-b2539dcb416e · outbound
This paper cites Large language models are zero-shot reasoners.
Neuro-Symbolic Data Generation for Math Reasoning Large language models are zero-shot reasoners
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.868134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e24a76b6-c439-4ee6-8014-4cfbcee8c338 · outbound
This paper cites Le, Ed H.
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.847181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c73d20fe-2dbf-4b7e-9040-5738a73c6c9e · outbound
This paper cites Le, and Ed H.
Neuro-Symbolic Data Generation for Math Reasoning Le, and Ed H
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.829072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 28e535df-8bf0-4ebb-b1cb-1cbf7f10cd89 · outbound
This paper cites Decomposed prompting: A modular approach for solving complex tasks.
Neuro-Symbolic Data Generation for Math Reasoning Decomposed prompting: A modular approach for solving complex tasks
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.784758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2a03de57-0846-4de7-9475-91df40287514 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models.
Neuro-Symbolic Data Generation for Math Reasoning Chain-of-thought prompting elicits reasoning in large language models
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.669194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 50f7397e-f281-4cb0-ba28-a6ed3f770169 · outbound
This paper cites Complexity-based prompting for multi-step reasoning.
Neuro-Symbolic Data Generation for Math Reasoning Complexity-based prompting for multi-step reasoning
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.557002Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 89532df7-e526-4f1e-abd5-67c0f76601c5 · outbound
This paper cites Automatic chain of thought prompting in large language models.
Neuro-Symbolic Data Generation for Math Reasoning Automatic chain of thought prompting in large language models
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.507462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 561b7257-f894-41b7-9f30-9cf476c8b15f · outbound
This paper cites Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning.
Neuro-Symbolic Data Generation for Math Reasoning Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.394140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation da406a29-a803-4629-9e3f-fa0ae58c175e · outbound
This paper cites Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning.
Neuro-Symbolic Data Generation for Math Reasoning Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.884758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d03a21a3-dd4c-4018-8d5e-9deff515f01d · outbound
This paper cites Teaching small language models to reason.
Neuro-Symbolic Data Generation for Math Reasoning Teaching small language models to reason
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.308018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 935cb7d3-2ab8-419e-a19b-efb21ddac176 · outbound
This paper cites Scaling relationship on learning mathematical reasoning with large language models, 2023.
Neuro-Symbolic Data Generation for Math Reasoning Scaling relationship on learning mathematical reasoning with large language models, 2023
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.940437Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5903c622-0fc9-4bfb-8c1f-fbf9421091aa · outbound
This paper cites Making Large Language Models Better Reasoners with Alignment.
Neuro-Symbolic Data Generation for Math Reasoning Making Large Language Models Better Reasoners with Alignment
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:13.954815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5ff79a7-cc11-4d0d-8480-b1db2c28e404 · outbound
This paper cites Large language models are better reasoners with self-verification.
Neuro-Symbolic Data Generation for Math Reasoning Large language models are better reasoners with self-verification
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.263024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 77cf220d-b6fe-4b19-a000-45358e91fe2b · outbound
This paper cites Forward-Backward Reasoning in Large Language Models for Mathematical Verification.
Neuro-Symbolic Data Generation for Math Reasoning Forward-Backward Reasoning in Large Language Models for Mathematical Verification
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.002541Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e1ca4c4-c369-49ea-bd6e-3cf059ffb15f · outbound
This paper cites Common 7B Language Models Already Possess Strong Math Capabilities.
Neuro-Symbolic Data Generation for Math Reasoning Common 7B Language Models Already Possess Strong Math Capabilities
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.025758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d0a9b698-f5d0-4a8c-927c-b150c37daf3a · outbound
This paper cites an unresolved cited work.
Neuro-Symbolic Data Generation for Math Reasoning Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T21:17:16.247875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3cb8dd79-48da-4ccb-8dcd-fe8154c6ff7f · outbound
This paper cites PAL: program-aided language models.
Neuro-Symbolic Data Generation for Math Reasoning PAL: program-aided language models
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.229210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 179efcd4-c288-48e0-adf9-b6e06a64940f · outbound
This paper cites MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.
Neuro-Symbolic Data Generation for Math Reasoning MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.055539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cc4bc7d-d601-44f0-85fb-0d28808253f6 · outbound
This paper cites Don’t trust: Verify – grounding LLM quantitative reasoning with autoformalization.
Neuro-Symbolic Data Generation for Math Reasoning Don’t trust: Verify – grounding LLM quantitative reasoning with autoformalization
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.208424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation af8e12f2-e23e-459a-9164-b93c22bac79d · outbound
This paper cites ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving.
Neuro-Symbolic Data Generation for Math Reasoning ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.068963Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 655f4159-558c-4483-9c09-ef50df050103 · outbound
This paper cites an unresolved cited work.
Neuro-Symbolic Data Generation for Math Reasoning Unresolved cited work
Reference 60
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T21:17:16.185625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d50fa9dc-0d23-4e0e-9488-d33845c02427 · outbound
This paper cites Validating smt solvers via semantic fusion.
Neuro-Symbolic Data Generation for Math Reasoning Validating smt solvers via semantic fusion
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.124535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ff268928-8edb-4a3a-932a-97710af8ea2f · outbound
This paper cites Curriculum learning.
Neuro-Symbolic Data Generation for Math Reasoning Curriculum learning
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.085850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8db102e1-7042-4344-b84d-7d2aeacae186 · outbound
This paper cites Curriculum learning: A survey.
Neuro-Symbolic Data Generation for Math Reasoning Curriculum learning: A survey
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.098313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91c85a4e-e35d-4efe-a0bd-df06939c95fe · outbound
This paper cites AlphaMath Almost Zero: Process Supervision without Process.
Neuro-Symbolic Data Generation for Math Reasoning AlphaMath Almost Zero: Process Supervision without Process
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.104930Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1a7ad6c-230d-47a3-be60-48db8454fcef · outbound
This paper cites Qlora: Efficient finetuning of quantized llms.
Neuro-Symbolic Data Generation for Math Reasoning Qlora: Efficient finetuning of quantized llms
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.058165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d0af4971-f51e-4382-9db6-4bafc702d17f · outbound
This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.
Neuro-Symbolic Data Generation for Math Reasoning Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:16.008447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 35713749-0cc3-404f-b52d-257ec3508b08 · outbound
This paper cites Stanford alpaca: An instruction-following llama model.
Neuro-Symbolic Data Generation for Math Reasoning Stanford alpaca: An instruction-following llama model
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.969298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cd1128f1-c8ee-4818-b211-303e8164ccde · outbound
This paper cites Pysmt: a solver-agnostic library for fast prototyping of smt-based algorithms.
Neuro-Symbolic Data Generation for Math Reasoning Pysmt: a solver-agnostic library for fast prototyping of smt-based algorithms
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.854757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1bf880e0-eced-474a-a222-9a7d9bb4a13b · outbound
This paper cites Array programming with numpy.
Neuro-Symbolic Data Generation for Math Reasoning Array programming with numpy
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.147370Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11955aa3-f16d-41b8-87d9-bfb404c0165b · outbound
This paper cites Xsat: a fast floating-point satisfiability solver.
Neuro-Symbolic Data Generation for Math Reasoning Xsat: a fast floating-point satisfiability solver
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.737452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 678a2f5c-4cb9-4e8f-af9c-3feb63bb427c · outbound
This paper cites Dl2: training and querying neural networks with logic.
Neuro-Symbolic Data Generation for Math Reasoning Dl2: training and querying neural networks with logic
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.711780Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ec0f87c4-7dc6-4e89-9d69-3a61b26adad2 · outbound
This paper cites Learn- ing with logical constraints but without shortcut satisfaction.
Neuro-Symbolic Data Generation for Math Reasoning Learn- ing with logical constraints but without shortcut satisfaction
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.681087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0e0cc592-d7d3-4411-81a7-b89a5070b478 · outbound
This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
Neuro-Symbolic Data Generation for Math Reasoning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 73
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-11T21:17:14.169527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e5bb501-da7a-40c5-a6be-f39c5f046786 · outbound
This paper cites Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.603520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 62d0b111-13b1-40dd-955f-5c509fa01f82 · outbound
This paper cites Limitations.
Neuro-Symbolic Data Generation for Math Reasoning Limitations
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.561669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 71e8655d-16ae-4455-9e97-f2be193a395c · outbound
This paper cites Guidelines: • The answer NA means that the paper does not include theoretical results.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not include theoretical results
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.500586Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 404ad06f-d5cf-4cf8-ad5b-383182caa2ab · outbound
This paper cites We will public the code, as well as the fine-tuned models, for the reproducibility.
Neuro-Symbolic Data Generation for Math Reasoning We will public the code, as well as the fine-tuned models, for the reproducibility
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.459412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation be5ca655-3ce3-4318-8148-2318916673e1 · outbound
This paper cites Guidelines: • The answer NA means that paper does not include experiments requiring code.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that paper does not include experiments requiring code
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.431976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 957e14c2-73a0-45a8-8d39-003d770fbed5 · outbound
This paper cites Guidelines: • The answer NA means that the paper does not include experiments.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not include experiments
Reference 79
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.407408Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation abb2b571-3957-4645-ad27-39063891fa1f · outbound
This paper cites Guidelines: • The answer NA means that the paper does not include experiments.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not include experiments
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.355328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a89c9ccc-83d9-438f-a612-973480b82ba9 · outbound
This paper cites Guidelines: • The answer NA means that the paper does not include experiments.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not include experiments
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.314623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8562cca7-5aaa-4653-9821-098f9c5e00dc · outbound
This paper cites Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.262774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6e4bc65b-e891-4760-9aa1-a17daef340b6 · outbound
This paper cites Guidelines: • The answer NA means that there is no societal impact of the work performed.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that there is no societal impact of the work performed
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.245146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9c750057-6440-4bdb-8c65-8378a0846eef · outbound
This paper cites Guidelines: • The answer NA means that the paper poses no such risks.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper poses no such risks
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.231562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fc4fd91d-3b39-4087-800d-feff4c89eb26 · outbound
This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not use existing assets
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.184763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4051880e-6d1a-47a4-844e-7d89300ba7b6 · outbound
This paper cites Guidelines: • The answer NA means that the paper does not release new assets.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not release new assets
Reference 86
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.134427Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6232d76f-ddf9-443e-b367-ca3cb8248d78 · outbound
This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects
Reference 87
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:17:14.334754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3db7910-709a-4422-b3e8-296c4b20d55b · outbound
This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.
Neuro-Symbolic Data Generation for Math Reasoning Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects
Reference 88
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T21:17:15.089094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
Observation fa841f16-f458-4531-b321-e2c6e00cf99c · inbound
LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient cites this paper.
LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient Neuro-Symbolic Data Generation for Math Reasoning
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:09:01.645942Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1fc62b6-3321-49b9-9bba-357dee2558d7 · inbound
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation cites this paper.
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation Neuro-Symbolic Data Generation for Math Reasoning
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:40:08.816339Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebc1d33e-eb06-49a7-abf3-cf94bd7f7522 · inbound
LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models cites this paper.
LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models Neuro-Symbolic Data Generation for Math Reasoning
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:00:47.705080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.