Paper Citation Record · LEDGER

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2506.08352.

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

pith.paper-citation-record.v1
2506.08352 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:20:04.678780Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:59:19.576331Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:59:20.245819Z

Reference resolution

39 of 39 outbound references displayed

verified exact3
verified fuzzy0
unresolved36
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 272ebcfe-1f8f-4e02-bb67-08c99c0226df · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.531101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7f36aa9-93b8-4d49-9525-5d6b05948d17 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.535414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b0d9c3d-2894-4745-b730-5bd98b02dded · outbound

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

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.539838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4b84f46-e077-46a5-9db9-efc96c47e476 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.544162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00a963dc-3b13-4c79-bf6b-7b83bbf47d59 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.548253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a1529fc-3e7b-4f6a-a4df-4bf54734bc29 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:20:05.371417Z

Source-reported events for the cited work

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

Observation 16979356-ba25-461f-81cb-6f5e52cc047e · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.556573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8e6e81-d943-450e-baf7-51d84f854a4d · outbound

This paper cites MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.560765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ac37695-4a6a-4568-9463-03073eb1f7fb · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.565239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ec5092c-7c20-4a8d-938b-1ff96df223af · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.569002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbffd299-bf73-4a6b-b182-a8d213c6a8c3 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:20:05.358128Z

Source-reported events for the cited work

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

Observation d38801c2-39f3-4180-9fc3-2f55b3c278c4 · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.577187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cf96254-e69d-4d87-9ec4-1dc36bfc518c · outbound

This paper cites Deduplicating Training Data Makes Language Models Better.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Deduplicating Training Data Makes Language Models Better

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.580833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68ab3260-0958-479b-a3f4-848fc9ad1db0 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:20:05.344557Z

Source-reported events for the cited work

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

Observation b305ec22-3d85-4cf9-bae8-e18f9d9e5705 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.588178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf6c5fa1-85b2-49ab-a248-e5411c7e1338 · outbound

This paper cites Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:20:04.997818Z

Source-reported events for the cited work

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

Observation 140bbccf-e11a-4e24-9f65-cd7739fa9b46 · outbound

This paper cites An Agent Framework for Real-Time Financial Information Searching with Large Language Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models An Agent Framework for Real-Time Financial Information Searching with Large Language Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:20:04.978818Z

Source-reported events for the cited work

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

Observation 29a3fc8d-b524-49aa-9c0e-dda24b238923 · outbound

This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Search-o1: Agentic Search-Enhanced Large Reasoning Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.598607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92813646-1c9e-4870-bf0b-c4dabd6bc7cc · outbound

This paper cites Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:20:04.945183Z

Source-reported events for the cited work

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

Observation 84d25b17-e487-4b6f-8001-21af97ae0466 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.606262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93168502-03f4-4ff0-9e39-87a3ed4056a7 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.610013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1db37f4f-5e60-43ea-8483-880d7b926626 · outbound

This paper cites GPT-4 Technical Report.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models GPT-4 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.613476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6b3d568-d5de-423d-93eb-f0190a41f966 · outbound

This paper cites Training language models to follow instructions with human feedback.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Training language models to follow instructions with human feedback

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.616819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ace5b02-7ace-44de-b839-4be17ea8c442 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Measuring and Narrowing the Compositionality Gap in Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.620506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a63eac7-0af9-43ae-87a8-395eaed6e158 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.624214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2ca605a-ff1c-4c0e-8ffb-51dfa1f49933 · outbound

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

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.627721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82dddd16-887a-4967-9bb8-4377fa39fb74 · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.631210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6895831-5c05-4759-82e2-952c8ab45ca1 · outbound

This paper cites ZeroSearch: Incentivize the Search Capability of LLMs without Searching.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.635328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bd47fbc-bb17-42d7-afc0-afce38792520 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.639001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 150b7e48-c53d-4473-815b-245e98b49ee8 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.642718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d915ff67-fb9a-4f14-9b5a-c3f97672622c · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.650029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8604f5-90f4-402a-988e-f436b5baa48a · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.654413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93df9836-5edd-4514-b5d5-c6b9338f4aa6 · outbound

This paper cites When Search Engine Services meet Large Language Models: Visions and Challenges.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models When Search Engine Services meet Large Language Models: Visions and Challenges

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.658459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ace32ffa-911a-472e-9669-47d599d66954 · outbound

This paper cites Qwen2 Technical Report.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Qwen2 Technical Report

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.663082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c8aba97-b7ae-4c83-9258-e661802f1359 · outbound

This paper cites Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.667236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5857bf5-1679-4112-8ac8-d787cb100892 · outbound

This paper cites an unresolved cited work.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:20:05.313265Z

Source-reported events for the cited work

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

Observation 208ce99b-2e60-4612-9b81-7d5f48aca265 · outbound

This paper cites FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.675057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3aa853c-7082-4071-a132-60f19e845ce3 · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.678780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43e1e3da-6df7-4613-9874-9c0c20062979 · outbound

This paper cites Transactions of the Association for Computational Linguistics(2022).

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models Transactions of the Association for Computational Linguistics(2022)

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.646409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation fae78f6a-d1dc-4850-b8a7-8f1286e5ff64 · inbound

Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Study cites this paper.

Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Study Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:59:20.466605Z

Source-reported events for the cited work

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