Paper Citation Record · LEDGER

DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2409.07703.

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

pith.paper-citation-record.v1
2409.07703 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

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

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:11:05.426462Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 556b8617-b887-420c-9d9f-a9e5dc970094 · inbound

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering cites this paper.

MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:13:21.510007Z

Source-reported events for the cited work

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

Observation 6ac936f5-fb79-48e2-bd01-7228f3861b4d · inbound

AIGS: Generating Science from AI-Powered Automated Falsification cites this paper.

AIGS: Generating Science from AI-Powered Automated Falsification DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T19:02:19.205839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1752b8ff-13f3-4cc9-8fcd-4e4633d46379 · inbound

LLM4SR: A Survey on Large Language Models for Scientific Research cites this paper.

LLM4SR: A Survey on Large Language Models for Scientific Research DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T21:39:25.314641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9f1506b-47f8-476e-9a70-d6933bd5a827 · inbound

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas cites this paper.

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T14:21:24.207266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c394ec0-35b5-4483-b58d-68e822601628 · inbound

Knowledge Augmented Complex Problem Solving with Large Language Models: A Survey cites this paper.

Knowledge Augmented Complex Problem Solving with Large Language Models: A Survey DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:02.033695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8e3e99f-d4a8-4c8c-837b-b7997b1f295b · inbound

Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale cites this paper.

Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T23:46:05.511997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92b8c99e-cd11-4231-aa52-2aff45fb1f1c · inbound

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey cites this paper.

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:19.482473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 680d5e7c-17ed-4fb0-acf6-b8a278b662e7 · inbound

A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications cites this paper.

A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 122

Resolution: unresolved; no resolver link, observed 2026-08-07T00:48:18.687246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dc316f9-9b24-4db2-ba4d-91110edf0c8b · inbound

RExBench: Can coding agents autonomously implement AI research extensions? cites this paper.

RExBench: Can coding agents autonomously implement AI research extensions? DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:37:08.910235Z

Source-reported events for the cited work

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

Observation 29f67b7d-f44c-4129-bee6-9aa70859ad81 · inbound

How Far Are AI Scientists from Changing the World? cites this paper.

How Far Are AI Scientists from Changing the World? DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T10:55:14.767959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ced49b2-0594-4fb0-b73a-b7d70dd1f1ba · inbound

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems cites this paper.

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:22:51.723943Z

Source-reported events for the cited work

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

Observation 8c38d0a1-04ad-458a-b419-d85138cecc80 · inbound

When Should Users Check? Modeling Confirmation Frequency inMulti-Step Agentic AI Tasks cites this paper.

When Should Users Check? Modeling Confirmation Frequency inMulti-Step Agentic AI Tasks DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:01:08.880129Z

Source-reported events for the cited work

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

Observation eca912e1-9d73-4bc0-85d2-2d10b6011d45 · inbound

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics cites this paper.

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T10:36:23.719056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d74ccfd-08f5-4225-9bd7-b1e1cabab3e0 · inbound

Pioneer Agent: Continual Improvement of Small Language Models in Production cites this paper.

Pioneer Agent: Continual Improvement of Small Language Models in Production DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:05:57.629860Z

Source-reported events for the cited work

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

Observation af41eded-bb0e-4eb2-8abc-cf6b3455f994 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:28:21.454611Z

Source-reported events for the cited work

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

Observation 59e0362e-e648-436f-9bf9-cdf127b21075 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-30T19:05:00.922116Z

Source-reported events for the cited work

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

Observation b5b6dc35-afad-4f3a-a9ad-81304e5c5a94 · inbound

Business Utility of Large Language Models as Exploratory Data Analysis Agents cites this paper.

Business Utility of Large Language Models as Exploratory Data Analysis Agents DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T23:35:06.978809Z

Source-reported events for the cited work

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

Observation bad12990-f483-4bfd-b131-ad9a330e0a8b · inbound

Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories cites this paper.

Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:37:37.766614Z

Source-reported events for the cited work

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

Observation beac2195-3282-423e-ba1f-9cd5fb55b36a · inbound

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games cites this paper.

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-11T20:19:27.650696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e60ba965-954f-40cf-8fd8-df45e7d62793 · inbound

CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents cites this paper.

CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T02:18:45.052883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b591d3f8-d4d6-4667-ac65-10452495c4e6 · inbound

Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery cites this paper.

Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T22:27:23.447307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66ebe250-73dd-4313-be8b-7aa0051acd37 · inbound

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering cites this paper.

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T01:39:47.560956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a08ed31e-8526-4070-9314-4202812caf50 · inbound

ExplainBench: Evaluating Code Explanations from Agents cites this paper.

ExplainBench: Evaluating Code Explanations from Agents DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T15:36:22.417125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f302c8f-b879-4bee-b4c2-ec405d920637 · inbound

DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments? cites this paper.

DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments? DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T14:25:46.442800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32a66a14-581f-4471-86f3-471890fd5658 · inbound

Recovering Wasted Compute in Autoresearch Agents cites this paper.

Recovering Wasted Compute in Autoresearch Agents DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T14:26:19.390627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0505398e-866a-4ed1-b3b9-e530c2833f49 · inbound

Scaling Automatic Research Agents via World Models cites this paper.

Scaling Automatic Research Agents via World Models DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T00:11:05.426462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.