Paper Citation Record · LEDGER

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks

As of 12 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2412.12544.

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

pith.paper-citation-record.v1
2412.12544 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:02:49.136412Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T19:44:16.630377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T19:45:04.026367Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy2
unresolved34
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a800bcb0-e18c-455f-a570-d9603dafaad3 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Evaluating Large Language Models Trained on Code

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.003312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e5b7a2-69cd-4459-bb23-2623ec7d1eb2 · outbound

This paper cites Language Models are Few-Shot Learners.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Language Models are Few-Shot Learners

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.008959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eafca4c4-2ddb-41b9-b016-a2b9b02c81bd · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.013460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84eb2e20-63b9-4888-ba44-1e520a754765 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.606443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 028caa16-6a0b-4e03-9073-459b4299933b · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.595703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 68dd5b42-1b16-4b66-917d-05124ab2452c · outbound

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

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.025518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a860e386-2c0d-4b84-9f49-597933e990fc · outbound

This paper cites Qwen2.5-Coder Technical Report.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Qwen2.5-Coder Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.029757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5749040e-26bd-4c90-883b-c66d790b121d · outbound

This paper cites StarCoder: may the source be with you!.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks StarCoder: may the source be with you!

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.033941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25c821fc-ecf1-4faa-8077-3eafe5b9ab6a · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Code Llama: Open Foundation Models for Code

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.037793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a1b28b5-3e89-467b-8ee3-bb02e40a2dde · outbound

This paper cites GPT-4 Technical Report.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks GPT-4 Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.041752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 976db66b-1995-456b-bfb0-14b46c2c6800 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.584955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 756b6b2a-a7e6-43c6-8c63-4df42cf6339d · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks ReAct: Synergizing Reasoning and Acting in Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.048665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aef592b1-4747-4c16-b348-4316955ba746 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.052231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1d687df-ea9b-4bff-9e70-53615bfc90f8 · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.055354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 882e9d16-b692-4e46-bf7d-cebbfad13790 · outbound

This paper cites Executable Code Actions Elicit Better LLM Agents.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Executable Code Actions Elicit Better LLM Agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.058496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d9430e4-d8a3-40c7-94b6-815fed1744d5 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.573366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 728c057e-ebaa-4380-a05a-10f1fd42b6cc · outbound

This paper cites Planning with Large Language Models for Code Generation.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Planning with Large Language Models for Code Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.064787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 844f7d1d-d080-4b23-aadf-e78609501c64 · outbound

This paper cites V., Zhou, D., et al.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks V., Zhou, D., et al

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:02:49.561732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 68077d9b-029e-468b-8bd2-5b4f4a4d152b · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.071672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7bea6a8-9cd1-4768-a02c-85d2dd1b0698 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.551188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b4f97cba-ca2a-46d0-9886-d5352627ab49 · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Reasoning with Language Model is Planning with World Model

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.078904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e39c9dcf-ef21-4609-b9b1-3494c95ea924 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.539911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b74b7e13-73bc-4eb2-ae61-aec01aa25923 · outbound

This paper cites Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.086467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e949af3-ba39-4513-acb4-9d99c1ad41f9 · outbound

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

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Teaching Large Language Models to Self-Debug

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.090479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b967d5dc-135c-4ad9-a075-962501b1dc42 · outbound

This paper cites CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.094559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19a858cb-1c7b-49a1-bf42-23ffd7a464a8 · outbound

This paper cites ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.098915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39c7da93-f167-43cf-bdf8-487a54bd114a · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.103043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f41ec7c6-88b6-4558-90ca-20026eee4a77 · outbound

This paper cites Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.106710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01f808d6-80d3-43a4-a3c7-ebdc88bae46e · outbound

This paper cites Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.111008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b103385-4db8-455e-b481-c2aa4baab246 · outbound

This paper cites RoT: Enhancing Large Language Models with Reflection on Search Trees.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks RoT: Enhancing Large Language Models with Reflection on Search Trees

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.114922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7f0c287-de79-44a2-8e54-1aab522b5804 · outbound

This paper cites an unresolved cited work.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:02:49.528673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 727de6bb-f086-46e3-bada-a927fe679d04 · outbound

This paper cites Planning In Natural Language Improves LLM Search For Code Generation.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Planning In Natural Language Improves LLM Search For Code Generation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.122083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dcbdc2d-a295-438d-ad05-1702f5c610a1 · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.125617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b37dd8a9-307f-4f24-be64-53af32354db0 · outbound

This paper cites J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:02:49.516842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f42dcbdf-0388-49bd-a5a7-14853d61b7a5 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.132747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85d4573e-c06a-4442-9b5a-4d9f38ae1723 · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T14:02:49.136412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6a345381-1630-4327-b8f6-f0051ca68f35 · inbound

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model cites this paper.

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-22T19:45:04.028003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.