Paper Citation Record · LEDGER

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction

As of 5 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2604.27221.

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

pith.paper-citation-record.v1
2604.27221 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-07T09:35:14.203293Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:46:29.816765Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

verified exact25
verified fuzzy12
unresolved2
parse uncertain0
malformed identifier2
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68d274b7-f7f5-4924-b905-2a4737e07481 · outbound

This paper cites Agents of change: Self-evolving llm agents for strategic planning.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Agents of change: Self-evolving llm agents for strategic planning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:41:27.461605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd85711e-bb5d-4af9-a048-cbe627f4392a · outbound

This paper cites ScrapeGraphAI-100k: Dataset for Schema-Constrained LLM Generation.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction ScrapeGraphAI-100k: Dataset for Schema-Constrained LLM Generation

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:41:27.458199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0926db9f-7f72-4c31-9765-eaf63c993f66 · outbound

This paper cites xbench: Tracking agents productivity scaling with profession-aligned real-world evaluations.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction xbench: Tracking agents productivity scaling with profession-aligned real-world evaluations

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.100948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f2c34d81-aac5-4c3a-99c3-0554f1e9e58e · outbound

This paper cites Mind2web: Towards a generalist agent for the web.Advances in Neural Information Processing Systems, 36:64335–64366.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Mind2web: Towards a generalist agent for the web.Advances in Neural Information Processing Systems, 36:64335–64366

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.107214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ee27280f-c0e3-4a85-af81-17bdef817652 · outbound

This paper cites Learning hierarchical procedural memory for LLM agents through Bayesian selection and contrastive refinement.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Learning hierarchical procedural memory for LLM agents through Bayesian selection and contrastive refinement

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:41:27.464818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 03cfa88f-3380-4801-86b7-5e7117bd6b48 · outbound

This paper cites A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:23:15.948876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4511e38a-ca4b-48d3-a4e6-812cffbec6f4 · outbound

This paper cites SAMULE: Self- learning agents enhanced by multi-level reflection.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction SAMULE: Self- learning agents enhanced by multi-level reflection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.110235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d6bc8a98-7347-4220-93d5-51bd3d8d2c29 · outbound

This paper cites Automated Design of Agentic Systems.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Automated Design of Agentic Systems

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:07:55.640311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dbb15a17-1bbf-4dcb-a611-74d1a3c0673d · outbound

This paper cites Deep Research Agents: A Systematic Examination And Roadmap.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Deep Research Agents: A Systematic Examination And Roadmap

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.873775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3f065da8-b189-48f5-b282-5044d7b9e6fa · outbound

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

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.912773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1f8fa79d-0ddc-4a24-9d4b-262fe3bf3377 · outbound

This paper cites InfoSeeker: A Scalable Hierarchical Parallel Agent Framework for Web Information Seeking.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction InfoSeeker: A Scalable Hierarchical Parallel Agent Framework for Web Information Seeking

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.956765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2df74b4f-4e82-4373-866d-d6092fde037e · outbound

This paper cites WebThinker: Empowering Large Reasoning Models with Deep Research Capability.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:14:25.573630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a1dfabac-6260-4dca-a458-5b6e9243ece8 · outbound

This paper cites Select-then-decompose: Adaptive selection strategy for task decomposition in large language models.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Select-then-decompose: Adaptive selection strategy for task decomposition in large language models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.908686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 60c70a91-b2d8-418a-bc27-ffcf12511fd8 · outbound

This paper cites Webglm: Towards an efficient web-enhanced question answering system with human preferences.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Webglm: Towards an efficient web-enhanced question answering system with human preferences

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.104089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c788712d-e6be-4adc-9105-8d6118f5b3b5 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction WebGPT: Browser-assisted question-answering with human feedback

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.965671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5acabaf1-d28f-4917-b30f-13ace2f06254 · outbound

This paper cites Scaling Large Language Model-based Multi-Agent Collaboration.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Scaling Large Language Model-based Multi-Agent Collaboration

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T09:46:25.942136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 56597987-4d7a-4f20-b0c6-f3347c5466a2 · outbound

This paper cites Reinforcement Learning for Self-Improving Agent with Skill Library.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Reinforcement Learning for Self-Improving Agent with Skill Library

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:05:30.615062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ba61da68-503b-40e8-ad44-11ad7c124141 · outbound

This paper cites Memento-ii: Learning by stateful reflective memory.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Memento-ii: Learning by stateful reflective memory

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.917582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d1675f23-f0e7-4947-952a-f8ba640f644b · outbound

This paper cites WideSearch: Benchmarking Agentic Broad Info-Seeking.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction WideSearch: Benchmarking Agentic Broad Info-Seeking

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.931278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd010298-d550-4fb5-a3ee-61755b35c141 · outbound

This paper cites EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.885665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4deb389b-8316-4456-9486-5fc187628d50 · outbound

This paper cites Memory in LLM-based multi-agent systems: Mechanisms, challenges, and collective intelligence.TechRxiv preprint.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Memory in LLM-based multi-agent systems: Mechanisms, challenges, and collective intelligence.TechRxiv preprint

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-09T04:20:07.016700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5abfff3b-68ee-4fe8-851a-8b4dd9116194 · outbound

This paper cites SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-12T11:39:12.115659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ca258133-595f-4e96-a17f-37a960e0a98d · outbound

This paper cites A-MEM: Agentic Memory for LLM Agents.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction A-MEM: Agentic Memory for LLM Agents

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.961180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1d4bca65-141a-4f41-ba5f-aa17f932ba8f · outbound

This paper cites Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T04:55:54.660411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8a4c8d83-992c-4634-add8-70a69d343745 · outbound

This paper cites Learning on the job: An experience-driven self-evolving agent for long-horizon tasks.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Learning on the job: An experience-driven self-evolving agent for long-horizon tasks

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.864275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f234dc70-d773-4085-a055-d4b8132f2f3d · outbound

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

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction ReAct: Synergizing Reasoning and Acting in Language Models

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:46:25.922621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f1bc25ad-6b8d-403d-9b44-a140e5a62f14 · outbound

This paper cites arXiv preprint arXiv:2602.16873 , year =.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction arXiv preprint arXiv:2602.16873 , year =

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.970369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 225f77b7-749f-4feb-92a4-c8e058161fdd · outbound

This paper cites G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.947080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9171e368-9c65-4897-af96-11c4027f885a · outbound

This paper cites AFlow: Automating Agentic Workflow Generation.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction AFlow: Automating Agentic Workflow Generation

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:10:57.950228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 95ca0606-1883-4d5f-8eeb-d533a362ff10 · outbound

This paper cites A survey on the memory mechanism of large language model- based agents.ACM Transactions on Information Systems, 43(6):155:1–155:47.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction A survey on the memory mechanism of large language model- based agents.ACM Transactions on Information Systems, 43(6):155:1–155:47

Reference 30

Resolution: verified exact; doi, observed 2026-05-09T04:20:06.987968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e0a08d1a-3eca-4d6e-b24b-349f8ad19c2c · outbound

This paper cites Memento: Fine-tuning LLM agents without fine-tuning LLMs.Preprint.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Memento: Fine-tuning LLM agents without fine-tuning LLMs.Preprint

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.131151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 06b891c2-84b9-49ee-8cac-001984282e80 · outbound

This paper cites Memento-skills: Let agents design agents.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Memento-skills: Let agents design agents

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:25.936672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 33a8b195-6ec0-42d5-a84a-65cf00b63bf1 · outbound

This paper cites Webarena: A realistic web environment for building autonomous agents.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Webarena: A realistic web environment for building autonomous agents

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.136964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 60619e58-735f-4a76-8660-5e47fb774c5e · outbound

This paper cites an unresolved cited work.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-05-27T08:18:49.115776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 641c782e-c84d-4534-a2ca-1446c9ad5029 · outbound

This paper cites AMD Zen processors 2019–2021.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction AMD Zen processors 2019–2021

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.113278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 217246f7-24be-4702-8ecb-1412cb29cb49 · outbound

This paper cites an unresolved cited work.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-05-27T08:18:49.121333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8da94dd6-5f29-4cc8-a802-47582aeb86de · outbound

This paper cites Row F1 =89%, Item F1 =96%.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Row F1 =89%, Item F1 =96%

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.124159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 67ade2a5-0b89-4e74-b06b-e5e3b3075983 · outbound

This paper cites Key insight:With 12 columns per row, single agents retrieve fewer than 50 rows and fill barely 20% of cells correctly.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Key insight:With 12 columns per row, single agents retrieve fewer than 50 rows and fill barely 20% of cells correctly

Reference 38

Resolution: malformed identifier; raw_fallback, observed 2026-05-27T08:18:49.143087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f0491cb7-fed6-4f42-b65e-c85c67b083c6 · outbound

This paper cites Search the official websites of both organisations (any paper with Seed-team participation counts).

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Search the official websites of both organisations (any paper with Seed-team participation counts)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.127950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 240f3b10-0458-4127-9020-2b7a436753b5 · outbound

This paper cites ByteDance Seed papers 2024 H1.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction ByteDance Seed papers 2024 H1

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.118359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5fa7bd21-8664-4b92-b020-eb77639785c9 · outbound

This paper cites arXiv date takes precedence.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction arXiv date takes precedence

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.133982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0a94e4a4-80c4-441f-a719-703c08e4d1be · outbound

This paper cites Result: 134 rows retrieved.Row F1 =91%, Item F1 =94%.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Result: 134 rows retrieved.Row F1 =91%, Item F1 =94%

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T08:18:49.139858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e5c622f5-2810-4189-bbac-405f18b396a6 · outbound

This paper cites Single agents retrieve fewer than 30 rows, missing the majority of Seed papers and most DeepSeek entries entirely.

Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction Single agents retrieve fewer than 30 rows, missing the majority of Seed papers and most DeepSeek entries entirely

Reference 43

Resolution: malformed identifier; raw_fallback, observed 2026-05-27T08:18:49.146254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation e5f8a348-971b-4ce2-a068-0187295278a1 · inbound

SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration cites this paper.

SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction

Reference 136

Resolution: unresolved; no resolver link, observed 2026-08-01T23:46:29.816765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.