Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:05:21.985940Z
Paper Citation Record · LEDGER
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers
As of 8 August 2026, this Paper Citation Record lists 100 of 101 outbound references and 3 inbound Pith citation observations for arXiv:2505.20128.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:19:01.924228Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:19:04.829030Z
Reference resolution
100 of 101 outbound references displayed
- verified exact2
- verified fuzzy26
- unresolved72
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c95bbf79-e5a6-4b03-a6f7-26c69e8f71ac · outbound
This paper cites Information retrieval on the web.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Information retrieval on the web
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:13.505390Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adc96400-63b3-4643-8c91-197ec2c2346a · outbound
This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers A survey on rag meeting llms: Towards retrieval-augmented large language models
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:13.604740Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e86b0207-e6cd-41d8-805b-c3f27b249e55 · outbound
This paper cites Retrieval augmented fact verification by synthesizing contrastive arguments.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Retrieval augmented fact verification by synthesizing contrastive arguments
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:13.720735Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e9c8b11-82d9-486c-8ca2-aa22fe4e5236 · outbound
This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:13.840604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 564ba6a6-d365-43b2-a249-e898b9ec5788 · outbound
This paper cites Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:13.961513Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b30c650b-9b93-4cf6-a783-8292f8ca3181 · outbound
This paper cites Is ChatGPT good at search? investigating large language models as re-ranking agents.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Is ChatGPT good at search? investigating large language models as re-ranking agents
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.101879Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f749abda-88f8-4111-8ce7-fba30db0e97b · outbound
This paper cites RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.209452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e5524f22-fa16-43d2-8eb2-dc1d7c5b6c32 · outbound
This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Retrieval-Augmented Generation for Large Language Models: A Survey
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.328036Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18022728-b1e8-404a-b9df-d7ac85703d12 · outbound
This paper cites RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.402328Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4242cff-c1ae-406c-ae82-a751886e402d · outbound
This paper cites Self-rag: Learn- ing to retrieve, generate, and critique through self-reflection.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Self-rag: Learn- ing to retrieve, generate, and critique through self-reflection
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.507323Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 403ecb68-2e9c-4c34-adf4-9ac812c4c61d · outbound
This paper cites Improving scientific document retrieval with concept coverage-based query set generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Improving scientific document retrieval with concept coverage-based query set generation
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.634542Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f116a78-3f50-4a84-83cb-59ae9feaffda · outbound
This paper cites Learning to Explore and Select for Coverage-Conditioned Retrieval-Augmented Generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Learning to Explore and Select for Coverage-Conditioned Retrieval-Augmented Generation
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:05:23.443794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3832d6c2-26d9-4e30-8961-94a402b53db2 · outbound
This paper cites Making Retrieval-Augmented Language Models Robust to Irrelevant Context.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Making Retrieval-Augmented Language Models Robust to Irrelevant Context
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.775773Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be3ea4e6-b631-45bb-9fed-7890a5240b3c · outbound
This paper cites Corrective Retrieval Augmented Generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Corrective Retrieval Augmented Generation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.872395Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae15d107-45ea-4c37-a614-45abd540b092 · outbound
This paper cites RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:14.960186Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23a6c6c7-fb03-47e1-82fd-822a0f25da3a · outbound
This paper cites Query rewriting in retrieval- augmented large language models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Query rewriting in retrieval- augmented large language models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.051634Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11d34376-c027-4b11-ac95-d51ec730818d · outbound
This paper cites ADELIE: Aligning Large Language Models on Information Extraction.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers ADELIE: Aligning Large Language Models on Information Extraction
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.142842Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 236c859c-c924-4d43-bced-2e6d90b8bf92 · outbound
This paper cites RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.221679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82c3bf84-21c7-4bcb-bbad-fe2e0acf35c8 · outbound
This paper cites Importance sampling: a review.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Importance sampling: a review
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.289783Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d4afa604-d503-4822-b424-27d49843da29 · outbound
This paper cites Looking for information: A survey of research on information seeking, needs, and behavior.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Looking for information: A survey of research on information seeking, needs, and behavior
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.371836Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d82cd82d-b496-452b-bfb6-320c3153a5ef · outbound
This paper cites Agentic Information Retrieval.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Agentic Information Retrieval
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.445008Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de230e1f-c273-4f83-b588-424b09be4c75 · outbound
This paper cites Exploratory search: from finding to understanding.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Exploratory search: from finding to understanding
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.501666Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2289089-a28f-42d8-a5df-f1e2c15e2312 · outbound
This paper cites The expectation-maximization algorithm.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers The expectation-maximization algorithm
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.550171Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e64856a3-434d-406d-928d-8e1ab369f88e · outbound
This paper cites Variational reasoning about user preferences for conversa- tional recommendation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Variational reasoning about user preferences for conversa- tional recommendation
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.619404Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c848aaf0-fccc-442c-85dc-f3e9b33d2bfb · outbound
This paper cites Variational reasoning over incomplete knowledge graphs for conversational recommendation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Variational reasoning over incomplete knowledge graphs for conversational recommendation
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.678807Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3871ef53-9b38-4752-8aea-40ca93b15aca · outbound
This paper cites Advances in Importance Sampling.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Advances in Importance Sampling
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.766679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 111f4eb8-d080-4cd4-9e19-8845b7a73e62 · outbound
This paper cites Axiomatisations of the average and a further generalisation of monotonic sequences.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Axiomatisations of the average and a further generalisation of monotonic sequences
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.818594Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5546e1a0-7a6b-41f7-9e8f-5c1a4eab3b68 · outbound
This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Retrieval-augmented generation for knowledge-intensive nlp tasks
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.869809Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4dec3ef6-87ca-430b-8990-5257c114f79a · outbound
This paper cites Search-in-the-chain: Towards accurate, credible and traceable large language models for knowledge-intensive tasks.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Search-in-the-chain: Towards accurate, credible and traceable large language models for knowledge-intensive tasks
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:15.955912Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4153c0c0-f540-4f13-b274-014d88e74e2c · outbound
This paper cites Stochastic rag: End-to-end retrieval-augmented generation through expected utility maximization.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Stochastic rag: End-to-end retrieval-augmented generation through expected utility maximization
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.054509Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49550ee4-072b-409a-a230-e445f23b84b9 · outbound
This paper cites Investigating the factual knowledge boundary of large language models with retrieval augmentation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Investigating the factual knowledge boundary of large language models with retrieval augmentation
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.146896Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ae85c51-3915-4eee-ab9e-5308abbc6be6 · outbound
This paper cites Natural questions: A benchmark for question answering research.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Natural questions: A benchmark for question answering research
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.199702Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f393b02-9174-4f78-bd8f-85660f61b316 · outbound
This paper cites Cohen, Ruslan Salakhut- dinov, and Christopher D.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Cohen, Ruslan Salakhut- dinov, and Christopher D
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:28.768832Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 465c7b3f-0f28-42d8-962a-899ac6ac6f5d · outbound
This paper cites MuSiQue: Multihop questions via single-hop question composition.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers MuSiQue: Multihop questions via single-hop question composition
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:28.580383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ff9f31fe-f667-47ed-81f5-63ccb0d00e45 · outbound
This paper cites Constructing a multi-hop QA dataset for comprehensive evaluation of reasoning steps.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Constructing a multi-hop QA dataset for comprehensive evaluation of reasoning steps
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:28.428699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e49d750b-c474-480d-8c43-8e400caf21a7 · outbound
This paper cites KILT: a benchmark for knowledge intensive language tasks.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers KILT: a benchmark for knowledge intensive language tasks
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:28.264514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e187fb5e-88f4-4351-ae83-436ade168513 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.476062Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34858bcb-ca8a-438e-a289-b78a58c72575 · outbound
This paper cites Introducing ChatGPT, 2022.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Introducing ChatGPT, 2022
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.524672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 133cff93-95cc-4b44-9dfa-8e63c60e23f7 · outbound
This paper cites Qwen2.5 Technical Report.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Qwen2.5 Technical Report
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.589932Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e88cab87-5c98-411d-89dc-ae764b56dbad · outbound
This paper cites Qwq: Reflect deeply on the boundaries of the unknown, 2024.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Qwq: Reflect deeply on the boundaries of the unknown, 2024
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.647669Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e31cba3-abf5-4f73-aaa1-94fb99280351 · outbound
This paper cites The Llama 3 Herd of Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers The Llama 3 Herd of Models
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.703077Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adc73a35-386a-4c74-a1b0-a813ee3a6fb3 · outbound
This paper cites Mistral 7b.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Mistral 7b
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:28.068583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 31cc3cf0-3695-4780-ab21-dec89dfa84e9 · outbound
This paper cites ChatQA: Surpassing GPT-4 on Conversational QA and RAG.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers ChatQA: Surpassing GPT-4 on Conversational QA and RAG
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:16.838616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd41e7e5-223b-4364-92d0-ba1398ce3c6a · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Direct preference optimization: Your language model is secretly a reward model
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:27.884301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 514f7c74-d7a2-4edd-bc04-0e566acf78c9 · outbound
This paper cites InstructRAG: Instructing retrieval-augmented generation via self-synthesized rationales.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers InstructRAG: Instructing retrieval-augmented generation via self-synthesized rationales
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:27.731300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 27ca1651-e090-489c-bab4-27216c6b16bf · outbound
This paper cites Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.020611Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0e106eb4-734e-405d-bff0-2044c139ca5d · outbound
This paper cites Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:27.533295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 03fdec90-2c6e-4fd4-9373-c6ba6bbd5e4e · outbound
This paper cites Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.111946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28e4d4fd-efb9-42c1-9c84-da1b3b43bda4 · outbound
This paper cites Generator-Retriever-Generator Approach for Open-Domain Question Answering.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Generator-Retriever-Generator Approach for Open-Domain Question Answering
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.173975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation faee4197-a6e6-40eb-8c83-81a5d6cc91f5 · outbound
This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Search-o1: Agentic Search-Enhanced Large Reasoning Models
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.295501Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6e93ec4-960b-4799-b03a-1543a5d4ef33 · outbound
This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.419701Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4109adfe-41ff-46d8-adbd-be3ed63b68a6 · outbound
This paper cites Proximal Policy Optimization Algorithms.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Proximal Policy Optimization Algorithms
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.509517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6a24f9e-d8af-46af-bb47-9394d1f92432 · outbound
This paper cites Khattab, Jon Saad-Falcon, Christopher Potts, and Matei A.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Khattab, Jon Saad-Falcon, Christopher Potts, and Matei A
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:27.306823Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f6587142-9a88-4ab7-be68-9023c302abfd · outbound
This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.716407Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e89b56f0-f66f-4bbc-8ce0-9d2d917c62a8 · outbound
This paper cites ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:05:22.961845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cc51be44-06e3-4767-8394-a48886d1eae8 · outbound
This paper cites Improving retrieval-augmented generation through multi-agent reinforcement learning.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Improving retrieval-augmented generation through multi-agent reinforcement learning
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:17.926793Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f17bb09-e43d-4c9e-9fbd-83fa26f1ce2b · outbound
This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:27.094615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3afe644a-310d-4720-b19e-8d830e577397 · outbound
This paper cites Mixtral of Experts.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Mixtral of Experts
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.095454Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd8cd45b-9b92-4beb-9d5e-47fb8bdd6049 · outbound
This paper cites Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:26.926645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 06dc0a60-0eb8-4833-b940-3f40b7d0a2f5 · outbound
This paper cites an unresolved cited work.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Unresolved cited work
Reference 61
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:05:26.795141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dc4cd457-e7bd-40c1-91a9-dd58cfd94a56 · outbound
This paper cites Document ranking with a pretrained sequence-to-sequence model.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Document ranking with a pretrained sequence-to-sequence model
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:26.609280Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 350f93f6-85b3-40d4-9501-402029d07eac · outbound
This paper cites C-pack: Packaged resources to advance general chinese embedding, 2023.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers C-pack: Packaged resources to advance general chinese embedding, 2023
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.496336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05d38201-8e9c-4ca5-b4c4-e8c583aaee30 · outbound
This paper cites RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.558566Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aaa81709-b90d-4fe2-8dc2-c629d0d6ce3d · outbound
This paper cites Physics of Language Models: Part 3.1, Knowledge Storage and Extraction.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.668363Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdc7e734-ab60-4aac-a809-488ad3eaf95a · outbound
This paper cites Information retrieval: recent advances and beyond.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Information retrieval: recent advances and beyond
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:26.353257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9a20189a-be06-43d6-a536-4e59b3468c92 · outbound
This paper cites Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.826562Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 962e23c2-5be7-44c3-a0af-8b5ac4f12143 · outbound
This paper cites Large language models for generative information extraction: A survey.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Large language models for generative information extraction: A survey
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.892905Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cbe1b398-96a0-4b10-af76-e5e33ef7818b · outbound
This paper cites Demystifying Long Chain-of-Thought Reasoning in LLMs.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Demystifying Long Chain-of-Thought Reasoning in LLMs
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:18.985725Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 873e8b5f-7c22-4b69-83dd-7f47a805c369 · outbound
This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.097980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df7ab4bd-f78c-405e-819e-b478340fa328 · outbound
This paper cites Xia, Quoc Le, and Denny Zhou.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Xia, Quoc Le, and Denny Zhou
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:26.122112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0a4b7a2c-ad48-4b13-bd84-4d8a6b1918dd · outbound
This paper cites Reasoning with Language Model Prompting: A Survey.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Reasoning with Language Model Prompting: A Survey
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.282572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68611013-2f1a-4d71-aa5e-e82cc35bbc04 · outbound
This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.390614Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a28bfe5f-fcc9-4719-9fc4-627aff186c07 · outbound
This paper cites Reasoning with large language models, a survey.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Reasoning with large language models, a survey
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.501659Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 745c6d4c-16b2-42cf-87a4-2134f481ee93 · outbound
This paper cites Thinking, fast and slow.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Thinking, fast and slow
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.566483Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf60d922-fc46-4c42-9e81-1078b21e22f8 · outbound
This paper cites Learning more effective representations for dense retrieval through deliberate thinking before search.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Learning more effective representations for dense retrieval through deliberate thinking before search
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.699152Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a8e76e5-4373-4881-9e15-045e5d0ef79e · outbound
This paper cites Tree of thoughts: Deliberate problem solving with large language models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Tree of thoughts: Deliberate problem solving with large language models
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.946846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b9c7efcb-3bbe-4964-afae-9b013e852031 · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.912405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6db7d1f-9cc8-4e6e-af76-db7bf03b8972 · outbound
This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
Reference 79
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:19.980478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ce54d20-9228-4fce-bc41-0c6183dc2f59 · outbound
This paper cites ToRL: Scaling Tool-Integrated RL.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers ToRL: Scaling Tool-Integrated RL
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.079725Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 043e0442-330f-47a7-a69d-40cc69fcc8d8 · outbound
This paper cites What Makes Large Language Models Reason in (Multi-Turn) Code Generation?.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers What Makes Large Language Models Reason in (Multi-Turn) Code Generation?
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.181133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2aed8c31-32d0-41d6-b11e-8775cac783dc · outbound
This paper cites A Survey on Large Language Models for Code Generation.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers A Survey on Large Language Models for Code Generation
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.249956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee6f0306-911a-4a87-97f1-9858001a6b9d · outbound
This paper cites In-context retrieval-augmented language models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers In-context retrieval-augmented language models
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.757113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 90954161-bac9-4aac-96df-e2156f63e600 · outbound
This paper cites Multi-level information retrieval augmented generation for knowledge-based visual question answering.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Multi-level information retrieval augmented generation for knowledge-based visual question answering
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.585253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 99c6a4c4-ac1e-404c-9774-4c117adfa27d · outbound
This paper cites Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods
Reference 85
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.556615Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c0b9061-af77-4eeb-8c8c-6927d53d6e75 · outbound
This paper cites The 37 implementation details of proximal policy optimization.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers The 37 implementation details of proximal policy optimization
Reference 86
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.416719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2416dc8f-1b34-47c4-863b-59cec1a61a9e · outbound
This paper cites Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
Reference 87
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.768390Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f4b8e15-5e15-4a2f-ad02-412bf176573e · outbound
This paper cites Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Reference 88
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.874472Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f60556ac-df75-4b36-bca0-634d49709598 · outbound
This paper cites Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge
Reference 89
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:20.983397Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 314c94a9-23a3-49de-b72c-4bc791ddc031 · outbound
This paper cites Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Peter J.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Peter J
Reference 90
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.233091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1dd17e79-8ded-4bbd-9def-ca1e8587e616 · outbound
This paper cites Buy 4 reinforce samples, get a baseline for free! In The International Conference on Learning Representations, 2019.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Buy 4 reinforce samples, get a baseline for free! In The International Conference on Learning Representations, 2019
Reference 91
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:25.086933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e1e96db9-c7f2-4856-ba4a-5b5ec1ae25b2 · outbound
This paper cites Sample efficient reinforce- ment learning with reinforce.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Sample efficient reinforce- ment learning with reinforce
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:24.913057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f791314f-9f7f-4579-82a3-2c2c52266bf3 · outbound
This paper cites Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:05:21.303489Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation edcf6b16-c05b-4cea-a03d-1406eefcc219 · outbound
This paper cites an unresolved cited work.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Unresolved cited work
Reference 94
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:05:24.679944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3571f04b-3892-4905-ae8a-ef7477920f2b · outbound
This paper cites Corpuslm: Towards a unified language model on corpus for knowledge-intensive tasks.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Corpuslm: Towards a unified language model on corpus for knowledge-intensive tasks
Reference 95
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:24.556898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b6bd6886-13ec-472b-934b-e0306a6b1a75 · outbound
This paper cites Rade: Reference-assisted dialogue evaluation for open-domain dialogue.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Rade: Reference-assisted dialogue evaluation for open-domain dialogue
Reference 96
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:24.433384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7846173b-5f85-4cbc-af8b-e625eef41164 · outbound
This paper cites an unresolved cited work.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Unresolved cited work
Reference 97
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:05:24.338093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7d4838ef-3190-40fb-b040-a0a7542ba834 · outbound
This paper cites an unresolved cited work.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Unresolved cited work
Reference 98
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:05:24.233494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1c8e330f-d459-4d5d-b8ed-9263db8c44e6 · outbound
This paper cites Please start with a special token ` < Final > ` followed by the final answer.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Please start with a special token ` < Final > ` followed by the final answer
Reference 99
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:24.068341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 73b575fb-650f-4c42-9a83-cd3d44211008 · outbound
This paper cites Godey ' s Lady ' s Book.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Godey ' s Lady ' s Book
Reference 100
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:23.891847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a750a2c2-4c68-47ba-beec-11fd01eb4669 · outbound
This paper cites Arthur ' s Magazine.
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers Arthur ' s Magazine
Reference 101
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:05:23.791676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
Observation 707e4ca1-d924-408b-b4ce-ec74d739b446 · inbound
DeepShop: A Benchmark for Deep Research Shopping Agents cites this paper.
DeepShop: A Benchmark for Deep Research Shopping Agents Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:19:04.942153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3d901d72-7360-4ee7-994c-5de564539b09 · inbound
SIGMA: Search-Augmented On-Demand Knowledge Integration for Agentic Mathematical Reasoning cites this paper.
SIGMA: Search-Augmented On-Demand Knowledge Integration for Agentic Mathematical Reasoning Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T06:57:15.870446Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51c984df-a44d-4418-a62e-672d1cb39fa0 · inbound
Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents cites this paper.
Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers
Reference 141
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T15:12:55.883703Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.