Pith. sign in

Paper Citation Record · LEDGER

ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.17645.

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

pith.paper-citation-record.v1
2401.17645 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

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

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:40:24.642904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:22:25.503508Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ff236ec8-a455-4eee-ab04-2d833e152c6c · inbound

Unsupervised Query Routing for Retrieval Augmented Generation cites this paper.

Unsupervised Query Routing for Retrieval Augmented Generation ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T20:40:24.642904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:40:24.642904Z digest=sha256:69d9d040b2738bda93d4aa342d6dcdc5192137c7034fe4bca679a7d0452513a6

Observation b8214ed8-5a2f-4a3a-aea2-596658c18a69 · inbound

Federated Retrieval Augmented Generation for Multi-Product Question Answering cites this paper.

Federated Retrieval Augmented Generation for Multi-Product Question Answering ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T14:46:04.366570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:46:04.366570Z digest=sha256:c157b650431cf14609d0be6ab5283c8dbfd03be35c756728fdaef2940b62a9c5

Observation 8fd4bb09-1512-409c-9da9-a9dddf84e1ca · inbound

Efficient Federated Search for Retrieval-Augmented Generation using Lightweight Routing cites this paper.

Efficient Federated Search for Retrieval-Augmented Generation using Lightweight Routing ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:22:25.506267Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-23T02:17:50.474681Z digest=sha256:2bbfe9e42a23c451dadad9d5a06fe2684915315aac54686fd80cd5257eb246be