Paper Citation Record · LEDGER

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

As of 4 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2604.22180.

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

pith.paper-citation-record.v1
2604.22180 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T10:30:26.342174Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:01:20.101304Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact16
verified fuzzy13
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80e148b4-ae1a-49dd-a576-668af239dd46 · outbound

This paper cites Large language models for information retrieval: A survey.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Large language models for information retrieval: A survey

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.854837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c6beaeae-e01d-4de1-834f-79234aa2a499 · outbound

This paper cites Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:01:10.868081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c331bf65-2146-4cbd-88f8-aa79cee6250b · outbound

This paper cites RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.884174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f680b3c2-6f4d-4a57-aa85-177d0e7e2a07 · outbound

This paper cites Lost in the middle: How language models use long contexts.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Lost in the middle: How language models use long contexts

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.314659Z

Source-reported events for the cited work

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Observation b06685a4-647a-4f1f-8a59-6cd1385faff6 · outbound

This paper cites Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.889588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f85d3fc7-d2e1-44eb-b352-571ed7c0ce48 · outbound

This paper cites Leveraging passage embeddings for efficient listwise reranking with large language models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Leveraging passage embeddings for efficient listwise reranking with large language models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.307113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 197a7639-ea11-42b0-abcb-99b7314d0e40 · outbound

This paper cites Visual instruction tuning.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Visual instruction tuning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.309719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 32d51cfe-f3e1-4a6f-964e-052717b91dc5 · outbound

This paper cites Compress-then-Rank:Fasterandbetterlistwisererankingwith large language models via ranking-aware passage compression.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Compress-then-Rank:Fasterandbetterlistwisererankingwith large language models via ranking-aware passage compression

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.304112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8d93fc7b-d7b4-448b-9824-799d58c85c6a · outbound

This paper cites E2Rank: Your text embedding can also be an effective and efficient listwise reranker.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression E2Rank: Your text embedding can also be an effective and efficient listwise reranker

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.874471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d216e89d-f2be-46dc-a2ec-e3f1db2c0093 · outbound

This paper cites Generatingdiversecriteriaon-the-flytoimprove pointwise LLM rankers.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Generatingdiversecriteriaon-the-flytoimprove pointwise LLM rankers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.312121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1a68bf68-c87c-4616-b321-eacd25c0a33a · outbound

This paper cites Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.897920Z

Source-reported events for the cited work

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Observation b6fca413-a255-4d93-b4da-b5336d5e21f1 · outbound

This paper cites Multi-Stage Document Ranking with BERT.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Multi-Stage Document Ranking with BERT

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.849655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a5f69255-79f4-4e16-9a87-c5d04387f4cc · outbound

This paper cites Document Ranking with a Pretrained Sequence-to-Sequence Model.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Document Ranking with a Pretrained Sequence-to-Sequence Model

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:01:10.862560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b2368ce5-2e98-4c8b-819f-9992b825deb6 · outbound

This paper cites RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T23:40:11.276075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a8563273-580c-4db9-add4-f8a2c30d8daa · outbound

This paper cites ListT5: Listwise reranking with fusion-in-decoder improves zero-shot retrieval.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression ListT5: Listwise reranking with fusion-in-decoder improves zero-shot retrieval

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.290943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b0a0a303-3404-47b6-8924-08e4f6ac8859 · outbound

This paper cites TourRank:Utilizinglargelanguagemodels for document ranking with a tournament-inspired strategy.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression TourRank:Utilizinglargelanguagemodels for document ranking with a tournament-inspired strategy

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.293244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d91b5cf6-6246-48c4-ba58-8943f5ea17ea · outbound

This paper cites DiffuRank: Effective document reranking with diffusion language models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression DiffuRank: Effective document reranking with diffusion language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.298134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation db559cc5-16d4-488c-a518-077234f5b232 · outbound

This paper cites jina-reranker-v3: Last but not late interaction for listwise document reranking.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression jina-reranker-v3: Last but not late interaction for listwise document reranking

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.279653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation cb2f225e-562b-43b2-94dc-d14954e224f1 · outbound

This paper cites Com- pLLM: Compression for long context Q&A.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Com- pLLM: Compression for long context Q&A

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.845242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3f7313e1-ce51-455d-a59a-7075b3891f23 · outbound

This paper cites Large Search Model: Redefining Search Stack in the Era of LLMs.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Large Search Model: Redefining Search Stack in the Era of LLMs

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.840611Z

Source-reported events for the cited work

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Observation 1690c5ee-4c9c-4bf7-bcb9-3f7117f65db0 · outbound

This paper cites OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-12T18:30:36.120082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 64e45d81-a188-4efa-a9c2-3593406bf4f0 · outbound

This paper cites KLIPA: A Knowledge Graph and LLM-Driven QA Framework for IP Analysis.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression KLIPA: A Knowledge Graph and LLM-Driven QA Framework for IP Analysis

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.813939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation aab7f71f-d7c5-4081-98dd-d977959f4699 · outbound

This paper cites HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:01:10.834350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8d4eb112-70a1-46cc-9a9e-0d7a1a540a63 · outbound

This paper cites RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:01:10.775550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8583e36c-a54a-4ee9-b0aa-9a2280c2332c · outbound

This paper cites Overview of the TREC 2019 deep learning track.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Overview of the TREC 2019 deep learning track

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:01:10.756970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e8179422-b234-4979-a60c-aebfd0ee5a60 · outbound

This paper cites Overview of the TREC 2020 deep learning track.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Overview of the TREC 2020 deep learning track

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T20:01:10.782839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation bd71a659-9951-406b-bd8a-e266a69340dc · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-12T14:42:11.637914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6364fd23-4256-48e9-abca-07ec9c29da68 · outbound

This paper cites Qwen3 Technical Report.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Qwen3 Technical Report

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-11T20:01:10.797136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 379931ca-55d9-470c-a432-a166065e6ae2 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-11T20:01:10.770476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3c1d32a8-4050-4683-a1b6-2c4e73d3b96a · outbound

This paper cites FlashAttention: Fast and memory-efficient exact attention with IO-awareness.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression FlashAttention: Fast and memory-efficient exact attention with IO-awareness

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.288263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation dac0f600-4d4b-4ee3-a336-741de4f5367c · outbound

This paper cites DeepSpeed: System optimizations enable training deep learning models with over 100 billion parameters.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression DeepSpeed: System optimizations enable training deep learning models with over 100 billion parameters

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.300988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ebb931a8-2fab-4bdd-a2f0-b743cf7f22f9 · outbound

This paper cites Reciprocal rank fusion outperforms condorcet and individual rank learning methods.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Reciprocal rank fusion outperforms condorcet and individual rank learning methods

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.282448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 42445113-571f-4195-bbfe-eb021abef6be · outbound

This paper cites The adiabatic theorem for non-Hermitian quantum systems with real eigenvalues and the complex geometric phase.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression The adiabatic theorem for non-Hermitian quantum systems with real eigenvalues and the complex geometric phase

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-30T02:16:10.847702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c35d5b56-fb94-469d-b3c6-23a56abaf654 · outbound

This paper cites Learning to rank using gra- dient descent.

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression Learning to rank using gra- dient descent

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:07:52.285424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Pith citing papers

Observation 111423ad-ba3a-4609-92a6-eb46f48c20dd · inbound

Structure-aware Relative Policy Optimization for Ranking cites this paper.

Structure-aware Relative Policy Optimization for Ranking ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T03:01:20.101304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.