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Paper Citation Record · LEDGER

Learning Agent Routing From Early Experience

As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2605.07180.

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

pith.paper-citation-record.v1
2605.07180 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:15:07.381414Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

  • verified exact10
  • verified fuzzy21
  • unresolved2
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch20

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1620208-5942-4ed4-af01-10994f6007a0 · outbound

This paper cites The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=.

Learning Agent Routing From Early Experience The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=

Reference 1

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.337972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:bcff2e89ad6054a5a78567900bc4058bbd0c3eff93b002abd8512d58f958bc9d

Observation 0439b031-9c94-4654-9ed4-3460999fc7a7 · outbound

This paper cites MasRouter: Learning to Route LLMs for Multi-Agent Systems.

Learning Agent Routing From Early Experience MasRouter: Learning to Route LLMs for Multi-Agent Systems

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T04:35:57.609237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:1df20595b3446431bff951ac672b6e0f9f6c1e84390ffbb02f5a7bcfbc02f222

Observation 32fc3d37-a1c9-4937-960e-0c121f89de38 · outbound

This paper cites Agentrouter: A knowledge-graph-guided llm router for collaborative multi-agent question answering.

Learning Agent Routing From Early Experience Agentrouter: A knowledge-graph-guided llm router for collaborative multi-agent question answering

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.641425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:06e85971af4cf6467963e9d3e1ef27515523548b0de91b2404f70a585a44ecbe

Observation 8ff5ee11-c075-41d9-9cdc-2695df288711 · outbound

This paper cites RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory.

Learning Agent Routing From Early Experience RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:35:57.713347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:4731c00bbd926027b60cf1dc5c5ab26b683a45bbe0d33c37a8bfd249248f6201

Observation 67161235-3b09-43dd-bf49-f3dfb43f213e · outbound

This paper cites Adaptive LLM Routing under Budget Constraints.

Learning Agent Routing From Early Experience Adaptive LLM Routing under Budget Constraints

Reference 5

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metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.457609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:a3d5b37ae1592fa54f6c4c8b27c2e7dcf72e67a041e0a90bdb56d07a021682a2

Observation 2a0a40f7-100f-4e0c-8409-11ed68b8365e · outbound

This paper cites arXiv preprint arXiv:2510.19506 , year=.

Learning Agent Routing From Early Experience arXiv preprint arXiv:2510.19506 , year=

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T04:35:57.434343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:56e30265fff4023e20bdc5d0d6d52649ba8585f01d0297af2d13eb789d17781d

Observation 0f64b902-0d4b-4e32-aaff-696c35fd5d00 · outbound

This paper cites Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation.

Learning Agent Routing From Early Experience Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation

Reference 7

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metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.493836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:702a7ef54a4318dcdc31cd363ed7c8c77d51f58fa513d2773b0d215ae2580f73

Observation 20dbead4-0591-49bf-b063-b4cee5714b73 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning Agent Routing From Early Experience Advances in Neural Information Processing Systems , volume=

Reference 8

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.328106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:d5fb8402fe99c95eaa03c7a396f738e83167ce39e863af1780db1c138864e60c

Observation aaa1026a-92f1-4842-bdbb-4ae231b4eff0 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Learning Agent Routing From Early Experience Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 9

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.621808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:acc9b92e227324d8d1d746fb1daa6f7343b5650d349124095415c9404ccf5481

Observation d803bc9e-71b0-4972-9353-b92a7e4e59b1 · outbound

This paper cites Self-improving llm agents at test-time.

Learning Agent Routing From Early Experience Self-improving llm agents at test-time

Reference 10

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arxiv_id, observed 2026-05-11T04:35:57.548438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:cdaeb46e2f7f49267944f4a31e3a04209f37265c3439b1c9ad0c5d54d75b3bd9

Observation 506667a1-1d5b-42e5-b27c-4c823f3c70ae · outbound

This paper cites Agent Learning via Early Experience.

Learning Agent Routing From Early Experience Agent Learning via Early Experience

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-26T03:04:06.268577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:3f684898f60b4b938eaaa31f479cd89d96790068aa3048110f81907c00960ac3

Observation 04d364ee-2ecc-4981-be64-47fd30a6e661 · outbound

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

Learning Agent Routing From Early Experience EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.536202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:2bde0935e8e3d47011c610801ad58850267870156f69303beb8c6a96ac96d4bf

Observation 2f0e22a2-a23d-483a-8b50-63b816784ea7 · outbound

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

Learning Agent Routing From Early Experience A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence

Reference 13

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metadata mismatch
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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:cbd0ad50837a19612e8d0877eb165d060859c1d65eda4fb5d9c9f3b055c88564

Observation 701a186e-ddb8-4127-b6a6-2a01ceb7ddb4 · outbound

This paper cites Advances in neural information processing systems , volume=.

Learning Agent Routing From Early Experience Advances in neural information processing systems , volume=

Reference 14

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.371743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:5cf48a330424527b627c354436c7e28f1cf1c349c7ff110a6b39319715bb088e

Observation a455795d-a9d5-434e-9ab2-0358095031d7 · outbound

This paper cites The eleventh international conference on learning representations , year=.

Learning Agent Routing From Early Experience The eleventh international conference on learning representations , year=

Reference 15

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.362433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:5310bbbe028e363562bb735ce84cab212e29ef77511af55e61649801ec0ff825

Observation 5e091af2-e50e-475f-907a-b28692797a5b · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Learning Agent Routing From Early Experience Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:44:37.129111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:e6169ca88b5f1dbbb6252b86e2d9e3635dfdd3bbdf5df8dc6a0a5ccd4b28ac5d

Observation 7645a7df-ad8f-4909-90a1-935488320833 · outbound

This paper cites Advances in neural information processing systems , volume=.

Learning Agent Routing From Early Experience Advances in neural information processing systems , volume=

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.357612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:cc6f5c8fd3bc8d378064f909002383fac5e75776da34f12607aae25b6379baf6

Observation badb2fed-2e72-407f-b593-ca49c71d65e0 · outbound

This paper cites Proceedings of the 2025 ACM Conference on International Computing Education Research V.

Learning Agent Routing From Early Experience Proceedings of the 2025 ACM Conference on International Computing Education Research V

Reference 18

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.385738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:90af062b498db2c2f758e40854d9d2b4052b3f318e3d5b4bba96c3fcb8fd220f

Observation 94353a3c-ed9e-449b-8a3d-b6a423901def · outbound

This paper cites Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response.

Learning Agent Routing From Early Experience Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.600634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:33ef396c410904a9da4d6994b2bd6d39e875f0711ee02dd5432cbc396032ab8f

Observation 7483cd9e-cccd-43e4-bd34-64e9223ee598 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Learning Agent Routing From Early Experience The Twelfth International Conference on Learning Representations , year=

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.412594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:aed779fbb4e4641595730ea43474ec8231635546942761684f61cc0cc4fa09ef

Observation 6e5cbbd9-67aa-48b3-8fa2-f4f2cdc2d739 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year=.

Learning Agent Routing From Early Experience Proceedings of the International Conference on Learning Representations (ICLR) , year=

Reference 21

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.380751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:53162c0f636481557c6a6b3028a7276e51bbc446ced8e5ac8b34a33f74c4edc0

Observation e5b25611-39bd-4e7b-a3ef-0f73850e5bd7 · outbound

This paper cites Memento: Fine-tuning LLM Agents without Fine-tuning LLMs.

Learning Agent Routing From Early Experience Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Reference 22

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metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.682196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:88fb478fb45a690ff1053541962fef4d8a65cce190a0ae047ac6351fe7130877

Observation c6ad22fa-6416-4151-967c-fe5f73f0421c · outbound

This paper cites OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation.

Learning Agent Routing From Early Experience OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Reference 23

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verified exact
arxiv_id, observed 2026-05-11T04:35:57.423223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:1da8f0c9b384e5e3f6b6b3291f164ba708cd60a361dd25616c006f7560b4c4a4

Observation b38cf815-ab42-4359-babf-0362e4ad07c2 · outbound

This paper cites Co-sight: Enhancing llm-based agents via conflict-aware meta-verification and trustworthy reasoning with structured facts.

Learning Agent Routing From Early Experience Co-sight: Enhancing llm-based agents via conflict-aware meta-verification and trustworthy reasoning with structured facts

Reference 24

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metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.739769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:b829711d28b50e52036cce024c9efdea04548078cb8494419283190870327fda

Observation cf7899c0-f167-4065-a8fa-36efb0d0f709 · outbound

This paper cites Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution.

Learning Agent Routing From Early Experience Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

Reference 25

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arxiv_id, observed 2026-05-11T04:35:57.587562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:08cb7c41315f8c7c92127f1115dcc40d348735b5202bbe59fa76e6dad57ab372

Observation 77d36efd-1ec7-44c3-bdac-9f9014100fcc · outbound

This paper cites arXiv preprint arXiv:2510.23601 , year=.

Learning Agent Routing From Early Experience arXiv preprint arXiv:2510.23601 , year=

Reference 26

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verified exact
arxiv_id, observed 2026-05-11T04:35:57.395354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:564f9fc996f23e1987ef6de43bf4d70da400d615d3e36bad6733c8a324aaa6a0

Observation 5a16178a-8353-4846-b522-4e3861852156 · outbound

This paper cites an unresolved cited work.

Learning Agent Routing From Early Experience Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-05-14T17:12:30.367094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:84a2035b8f39aac0300132b7652b4de97d62ce4c2909a39de743b55c48a3f9ba

Observation 7e24e9a1-614a-48c4-8058-ffd5752446ea · outbound

This paper cites 2024 , url=.

Learning Agent Routing From Early Experience 2024 , url=

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.347904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:591a67d177a34a7c028e6f784617461cd300e57acf11ceedade1d899a1f6ef27

Observation 4e6e1ef8-d1cd-4fbe-b51f-75a80caede87 · outbound

This paper cites Nature Methods , pages=.

Learning Agent Routing From Early Experience Nature Methods , pages=

Reference 29

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.342381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:d07f5f3a6946759d807e65796ca99da1bb10f46696288bcb07066c05bbd7c083

Observation 70ef9493-a5a9-436a-99c6-39b266669c97 · outbound

This paper cites Nature Computational Science , pages=.

Learning Agent Routing From Early Experience Nature Computational Science , pages=

Reference 30

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.390135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:777c1ce5b79dc1a404979ce732da7847a4d9cd06602fbcc06a3c45dc174bfa4f

Observation c6bb9656-62fa-4fc3-8202-419ba3efec1d · outbound

This paper cites an unresolved cited work.

Learning Agent Routing From Early Experience Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-05-14T17:12:30.316046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:8d9089e5dda7e71673e670330cae8ae88e5b8e380788d6b7f49f66690ba76f4d

Observation ef343a86-5934-47df-9083-f81aaa8f9e99 · outbound

This paper cites On Path to Multimodal Historical Reasoning: HistBench and HistAgent.

Learning Agent Routing From Early Experience On Path to Multimodal Historical Reasoning: HistBench and HistAgent

Reference 32

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verified exact
arxiv_id, observed 2026-05-11T04:35:57.472272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:d69a4ea931840a9cdcca1afdeb8ff723b46ae2354c9f6b471550752606139197

Observation e58897a4-1483-48d2-88ac-ede9192217f5 · outbound

This paper cites 2025 , note =.

Learning Agent Routing From Early Experience 2025 , note =

Reference 33

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verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.397745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:f3ac92387aa1e6cc6eb584bd76e292f60d480ba979b987ae518502a9b94276b9

Observation 7fb040f1-05ed-42b3-be12-6594f6f8061e · outbound

This paper cites Universal Model Routing for Efficient LLM Inference.

Learning Agent Routing From Early Experience Universal Model Routing for Efficient LLM Inference

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.517116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:4c635e30c51ad9f5c6a3251e7d967ccf9592e94cdc3b7328ca4ce7652a7cec6b

Observation df4ea24e-22cd-4406-aaf6-2e59531e8a9a · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

Learning Agent Routing From Early Experience Large Language Model Routing with Benchmark Datasets

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.726716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:0fc2b4c84b6ef0f741ac536c063d868e26e0bfa96e97e822535a73e6752a7acb

Observation 9b338d22-0e31-42f9-a942-f67d0b5cab59 · outbound

This paper cites BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute.

Learning Agent Routing From Early Experience BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:35:57.654049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:7b9e7d94198bd6c243d7cefc8aa45959cbe73bb0ed05823c38db310e48abd951

Observation dc6b61eb-a722-4752-80f0-fc552d8fd7c0 · outbound

This paper cites Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models.

Learning Agent Routing From Early Experience Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models

Reference 37

Resolution
verified exact
doi, observed 2026-05-11T01:15:50.850285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:e0392d0e6a9498c57fb5618322cb2b89308ddaf311fdee3a050f08edbde1f17e

Observation 4fcf753f-622e-47b3-855e-ef35b50a1fcb · outbound

This paper cites 2025 , month =.

Learning Agent Routing From Early Experience 2025 , month =

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.402119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:5d1b9cc9bded81489a63fa9f24b5c923ac9a089193adae25cf9e1fa5e1975420

Observation 4d88752f-eae6-4015-8095-fc6775118148 · outbound

This paper cites 2025 , month = dec, url =.

Learning Agent Routing From Early Experience 2025 , month = dec, url =

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.313088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:7d5ed2d2e983f98856525d125c2a85015e8a94b26f40f9766d3445948f0f981a

Observation c49c6c70-ec5f-47aa-af1a-28b65c3d17a4 · outbound

This paper cites an unresolved cited work.

Learning Agent Routing From Early Experience Unresolved cited work

Reference 40

Resolution
parse uncertain
raw_fallback, observed 2026-05-14T17:12:30.407083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:c4740300515b78c78a70084a340c6852a3f4231d418ff9de5a8f69b33a69808f

Observation 8976848f-a9ad-4acb-a9bd-586f77de5872 · outbound

This paper cites 2025 , month = dec, howpublished =.

Learning Agent Routing From Early Experience 2025 , month = dec, howpublished =

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.352557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:a193a423122a54ea1f855d8b6d4f9e2ce55ed1c816c2d5b1645d1833b149bae0

Observation f55aabae-618c-4cb4-bd06-45b047ca3e49 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Learning Agent Routing From Early Experience Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 42

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.505232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:c8a5b7a1da53e9d7416cd72f5859f6d7bd4960a2b5cbb4fe6fe14c78af4800a1

Observation 32301a6a-98f8-4b01-bc4e-fa2f279d46e7 · outbound

This paper cites 2025 , month = may, url =.

Learning Agent Routing From Early Experience 2025 , month = may, url =

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.375968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:de8955d05cf88332c352ff272c84c37d34a742cf8701006425e0017e7431a854

Observation bffec02f-8d1e-4e62-819b-e373dcf12bae · outbound

This paper cites 2025 , month = sep, howpublished =.

Learning Agent Routing From Early Experience 2025 , month = sep, howpublished =

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.319301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:d5bdaec3f272acaee93def972070855b3a3ed8ca8ec6ae270dc0ddd4371a4680

Observation ff2630f5-1b22-4db9-9895-4527f04e5900 · outbound

This paper cites 2025 , howpublished =.

Learning Agent Routing From Early Experience 2025 , howpublished =

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.332994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:0885ea8145c09d63d82416277aa7735d55f71eee6a27b72a26f8b1a5ada7e278

Observation 089e3355-2934-4d86-85cc-a341199410df · outbound

This paper cites Qwen3 Technical Report.

Learning Agent Routing From Early Experience Qwen3 Technical Report

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.524807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:08e20025ebea8e2c9e93ec87112803defc4adf5376a6ac8c20932aace43e4004

Observation 0200fa49-470b-4303-9566-cb8f31697b8c · outbound

This paper cites 2025 , month = jul, howpublished =.

Learning Agent Routing From Early Experience 2025 , month = jul, howpublished =

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.394040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:0296c329d8ed9c8315bb9c2287a057677de669d1428b31c81bedfef54b031579

Observation bb0ff3f7-5cfb-4489-86f4-40b393f368fc · outbound

This paper cites DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models.

Learning Agent Routing From Early Experience DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-05-11T04:35:57.670174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:bb9cc462917e0ad96f068780a2d5dc52244173d1324b461580b17ededf63e4af

Observation 7a12eef5-cff1-4648-9074-f176487171ec · outbound

This paper cites 2025 , month = nov, url =.

Learning Agent Routing From Early Experience 2025 , month = nov, url =

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.417198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:0bb7d26af9794d7a0bd0d89956a9255fbcd0ec965b8ff9bf9aec5356a6193a8b

Observation cb6b505f-6053-4dbe-bb06-d49d1cbcafbc · outbound

This paper cites GPT-4o System Card.

Learning Agent Routing From Early Experience GPT-4o System Card

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.662121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:4232a58afbbe2780671d580882fa7621edaee2f1150b0b1be58ae9631cc919b9

Observation c8a33d23-5cc0-499d-8650-ae19a56efd6c · outbound

This paper cites author =.

Learning Agent Routing From Early Experience author =

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-14T17:12:30.323404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:1bb4cac56ac26319f7344ffa6a3f845275cf2e2356841c5e4d3151d751c2464c

Observation 8f30cfd5-972a-491c-acfd-5c3507a7704e · outbound

This paper cites Humanity's Last Exam.

Learning Agent Routing From Early Experience Humanity's Last Exam

Reference 52

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.568032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:985f84919a27d067500c6b3053b343d49e3d8308e0684edc57be03728f346e9f

Observation d23cacd4-fe6d-43f6-99ca-8681783460b4 · outbound

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

Learning Agent Routing From Early Experience LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 53

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T04:35:57.410386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:8a86c72ea2e2600b4482f5fbeb147e0404dc227807b4c3823a6d0633c3777d83

Observation ff2e6df0-3fdf-4514-b7d1-39f8e5d60074 · outbound

This paper cites AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes.

Learning Agent Routing From Early Experience AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:35:57.749352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T01:15:07.381414Z digest=sha256:3c3d28fee5ae18e276b0283e2684c13a99e7cf6f9009c3590aa41b24d2fa7233

Pith citing papers

No inbound Pith citation observations are available.