Paper Citation Record · LEDGER

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2607.05441.

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

pith.paper-citation-record.v1
2607.05441 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T01:37:34.939545Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

16 of 16 outbound references displayed

verified exact0
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa8608b4-2648-4ccb-9a7e-43e7d41d11a4 · outbound

This paper cites Perception Encoder: The best visual embeddings are not at the output of the network.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Perception Encoder: The best visual embeddings are not at the output of the network

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18919b1a-b8a5-49fb-8071-420065672f96 · outbound

This paper cites The Llama 3 Herd of Models.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models The Llama 3 Herd of Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 672bebe0-1c63-4b60-83e1-270241843180 · outbound

This paper cites In AAAI, pages 18030–18038.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models In AAAI, pages 18030–18038

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dab1c06-ed3a-49d4-bffd-f432d0394feb · outbound

This paper cites ORPO: Monolithic Preference Optimization without Reference Model.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models ORPO: Monolithic Preference Optimization without Reference Model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a572e4a1-7169-4df0-b8ec-d7c92e13a1e4 · outbound

This paper cites Gautier Izacard, Patrick S.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Gautier Izacard, Patrick S

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eca43ef-84ad-4909-a517-b68601b5a92a · outbound

This paper cites Mahmut Kaya and Hasan Sakir Bilge.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Mahmut Kaya and Hasan Sakir Bilge

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f426159-b11d-4f8f-bf29-acdf2a32c7a0 · outbound

This paper cites TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8965bb6d-4886-46fe-a96f-3cd8d72debca · outbound

This paper cites InEMNLP, pages 3102– 3116, Singapore.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models InEMNLP, pages 3102– 3116, Singapore

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c6f190d-c0a5-4bb5-a3c8-2b621bcbc910 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 709a8c07-159e-4ff0-bf9c-b316c094fcda · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ba3a732-32ca-4411-a316-882072acd63d · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Gorilla: Large Language Model Connected with Massive APIs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0706541-7379-4bea-b93b-35119c0e272c · outbound

This paper cites Making Language Models Better Tool Learners with Execution Feedback.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Making Language Models Better Tool Learners with Execution Feedback

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 709e9fd1-ef2a-471b-975e-942a839fb097 · outbound

This paper cites InNeurIPS.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models InNeurIPS

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f84757-3104-4482-aad1-0e0e4c221e20 · outbound

This paper cites InICML, volume 202 ofPMLR, pages 31210–31227.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models InICML, volume 202 ofPMLR, pages 31210–31227

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b9eed6b-a834-42aa-8dfd-057ced8977f7 · outbound

This paper cites RestGPT: Connecting Large Language Models with Real-World RESTful APIs.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models RestGPT: Connecting Large Language Models with Real-World RESTful APIs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bda9c32-a658-44e8-bc0e-e7bed600f9d1 · outbound

This paper cites Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models.

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models

Reference 16

Resolution: malformed identifier; no resolver link, observed 2026-07-12T01:37:34.939545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.