Pith. sign in

Paper Citation Record · LEDGER

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis

As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.18710.

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

pith.paper-citation-record.v1
2505.18710 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:30:56.248436Z

measured 39 of 39 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

39 of 39 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa7a07b4-38b9-4a05-9f0e-7ba932e97873 · outbound

This paper cites online" 'onlinestring :=.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis online" 'onlinestring :=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:52.656266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:52.656266Z digest=sha256:1ca11b55358fb0ccbc57afe9dfd9ffedc140a0d33b781d1924d153da08f21883

Observation 827cc3ec-7073-4edf-848c-916604b681f8 · outbound

This paper cites write newline.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:52.744638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:52.744638Z digest=sha256:efbbe9b997c05a1eb9da8eb256c2f75af090afecab63c60ed731bd3fe06e673e

Observation 87afa78c-e2da-4f02-8807-e3cc02f209ef · outbound

This paper cites GPT-4 Technical Report.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis GPT-4 Technical Report

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:52.824716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:52.824716Z digest=sha256:1e214978db0f3afc07a53a7bf03f214e01bbdd9413059d08389b21a321760386

Observation 601b515b-1d0b-4725-ad7a-786a0b5938af · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:52.906135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:52.906135Z digest=sha256:86a343f433261e556e0e8306bba020678b3646f9a6b7c2c7116b5891bb37532d

Observation 88cf084c-d5db-4e09-8c81-fdfbb46acf90 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:52.991748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:52.991748Z digest=sha256:2040ccce643f2a3a22bbdfcaaf1fdc3d84dd8609c115f3e368c7df32d96c613f

Observation c2e10192-1437-4c0c-bc53-7e0f3a3f83d8 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.066347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.066347Z digest=sha256:299ab413ea9f3481d29f46d1811e1cd31dd78b9ef7a35f61cbe550d28a9bbd70

Observation ad9cd22b-fbbe-4ebb-9c00-2c8b7f58c2fc · outbound

This paper cites Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.191782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.191782Z digest=sha256:07c0c7dc8ca853d8e3db9db546a08cd23f4fb8e9f12ed7782dc37d322c8e53af

Observation f49228e1-a807-43db-9428-ac8d35c7c656 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.268669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.268669Z digest=sha256:ca597c8b238f5e08a8c101725f2220a4a8e3afa7279ede76db2ad31cf52761a2

Observation 18ce72a4-bd86-4e42-8d56-c5081cd4c15c · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.364959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.364959Z digest=sha256:af59b556eba1f9842b75b78db90a9a97fab42e4b616a0cdfac907bddac95061e

Observation 76782d3d-30a3-4beb-8af6-18bac0c54bf3 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.493153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.493153Z digest=sha256:311bab20dc420366365bb2166c47068cb1fb6ca5f61b383afb4ea3a31b737f54

Observation a6f8e021-66f6-4ce1-ad52-d60167946a12 · outbound

This paper cites Rethinking with Retrieval: Faithful Large Language Model Inference.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Rethinking with Retrieval: Faithful Large Language Model Inference

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.569078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.569078Z digest=sha256:0e3d92a6a0b709745cc0f32dc2877b1f6e7443d6c5793eb2c31265b21110d07d

Observation 8fd37d16-3671-4b6d-ac6b-9315399543ae · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.778386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.778386Z digest=sha256:fcb0a24a411847de655ee61e2c23f18e5063ac8eafe0ceeb676cf9d1ed530a2c

Observation d4d33b04-423b-4b82-9ef7-5e07ef3b272f · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.863306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.863306Z digest=sha256:349102674b3e27819f63d86bbc0ec04a99f40c434fbdc55a0e1e5606c95ea5b6

Observation c9d7a0dc-c480-4619-a58c-a5a6acce4039 · outbound

This paper cites Atlas: Few-shot Learning with Retrieval Augmented Language Models.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Atlas: Few-shot Learning with Retrieval Augmented Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:53.935877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:53.935877Z digest=sha256:8da8ef4e4b3de2251a7cb97144f4ce6fe37426666cb649a35597aa4d8e516e41

Observation 6558374a-5019-4a13-8cc3-5da717212d2e · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.049064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.049064Z digest=sha256:463abde07813bba2ac11a453a2031facdb13e80dc7f2e8722e8b8f4308279e16

Observation 165378e4-0ccf-4964-a194-3fffa7d9d5d2 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.180427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.180427Z digest=sha256:8bf02359ea4d20d4081f487e9d81d578c1f4395fe9d665fc0dc7cd8c1f656df0

Observation ff323985-0754-448b-8c2d-e81093071341 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Dense Passage Retrieval for Open-Domain Question Answering

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.311608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.311608Z digest=sha256:fc6a2525107333f50d146a13b7f76d669fb3840f0f3eadb42186510300d6e390

Observation 1affa6fc-d9f7-4c14-92e9-8bc5a265ddf3 · outbound

This paper cites Bridging the Preference Gap between Retrievers and LLMs.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Bridging the Preference Gap between Retrievers and LLMs

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.419840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.419840Z digest=sha256:49a2b6a910cc0d70f123df9539a009a52fbef55c050f1ed9841e215eaade41ef

Observation 4bcc27a7-6561-4d05-9ee4-67b563263318 · outbound

This paper cites SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.525693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.525693Z digest=sha256:d1615d1c63a2adbb45adab096ef219f7dc05fa336035f4a537319a45e3a76615

Observation e03c58cc-7794-4f8d-9ded-fdb2dad4336f · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.617743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.617743Z digest=sha256:782cc34cc75248558e1458c7df221bc3f2a74594c635e3aa404447d19ec44122

Observation ce72a03e-1f67-46df-858f-b73c9e180a73 · outbound

This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.732812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.732812Z digest=sha256:7f27c63a1c96d3c5a34d6a0a63d5099a39c041b347fa798e8d7eaa38c5f76072

Observation c2327ce6-34a5-4800-bd70-56a1f7ae1353 · outbound

This paper cites Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.840814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.840814Z digest=sha256:1167c49836d025e6017cf48c9a5e8c6ec6e4b08ea5b45af2cc82d7d744bda072

Observation 12b92e94-51eb-4fd0-80d3-53314c049101 · outbound

This paper cites From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:54.951220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:54.951220Z digest=sha256:70ad7e5132571230f68c457b29c8fe09aeab0c4e1ff5315ebbea214346aed4f0

Observation 6b8c7b36-ca21-4f30-817a-bb3f80a2c3d6 · outbound

This paper cites Contrastive Decoding: Open-ended Text Generation as Optimization.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Contrastive Decoding: Open-ended Text Generation as Optimization

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.026727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.026727Z digest=sha256:3447da58d32d1cc1a594fa3238a7c6f67067d1fba1bac4087cb343594c9f10eb

Observation c82370a8-376d-4f87-9573-92c31dbfc723 · outbound

This paper cites RA-DIT: Retrieval-Augmented Dual Instruction Tuning.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.094747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.094747Z digest=sha256:70cb02e36bc91c3fe6502b1e006ca8db885acf850d1d62c246b20ccf0271c18e

Observation 1b6e3abe-38bd-4c22-a3a9-ce02adda65d7 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.234743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.234743Z digest=sha256:47512f26e7a7ffb04ba6b04d79f39f4a382b3430dc8cb9ec70e41a8089073bf3

Observation 6644aa7a-a242-43bd-aaa4-08d46ab6867e · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.288600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.288600Z digest=sha256:7ecf68d1e48dcd3cf8a70ccaf25a11111ef8615c1c65d7b90ef0f2b5d8a4fed7

Observation adb12687-863a-41ea-bbd9-217a2d1eb359 · outbound

This paper cites W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:30:56.488179Z

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=2026-08-07T14:30:55.381245Z digest=sha256:6d979708e5843c871735c7838b25f990538a6ce7d4364a114fdcdb1c3184c80b

Observation f1c7f738-b0b5-468d-8338-edba84b03221 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.450490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.450490Z digest=sha256:b330e3b3c13bf3b0d82366636ecef70a7f0cc2e33dd6747d6b394f483bae7ef9

Observation acc833d7-0d8b-4748-ab72-e0eb79b56a70 · outbound

This paper cites Trusting Your Evidence: Hallucinate Less with Context-aware Decoding.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Trusting Your Evidence: Hallucinate Less with Context-aware Decoding

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.518056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.518056Z digest=sha256:3ab98f5af2cfa8155452892298dc5d569c77eac3830c8f79604ac6091e8d2ac0

Observation 20ff52fd-7335-4fac-b45c-d3d2a277dfc6 · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.611939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.611939Z digest=sha256:b8a6c02c3eccfb403de25a410e9a354403ff41fc32a492d94fcf96ee47b4517d

Observation f4c7dd07-665b-4c20-96cb-95d596040a73 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis LLaMA: Open and Efficient Foundation Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.659579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.659579Z digest=sha256:b3ea42158a3981146488cd60427624b1bcc5357777ae0766a7413553560b6324

Observation f38dd14a-f8b5-4e7f-8037-cc43e4becb77 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.744806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.744806Z digest=sha256:deea2a76d43fa0a09c427253c33ac45858b73738b2f3d7f66d29226274fcc7a5

Observation 087cf98d-516d-47ff-aa06-ab6025e330e6 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:30:56.776049Z

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=2026-08-07T14:30:55.826272Z digest=sha256:7460c03f9fe04c0ecf347ff13bd899121f3fe92b4f4088c116d0818cfef5ab06

Observation ffe53512-5524-44d4-b874-201c9dc22e7a · outbound

This paper cites REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:55.881903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:55.881903Z digest=sha256:cc544ec508d47313f0db639181360ab16da46a7fa8a13fc829bf99ad93b95d05

Observation 8605a773-ab50-49ec-9faa-d3a67b960120 · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:56.006069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:56.006069Z digest=sha256:48d61b5d298fd57bac3a35cb7afafe6fab6c51c5c9b26941664e0801b6251c89

Observation 0b2bf267-3578-454e-a3cf-55b80cbbc04b · outbound

This paper cites an unresolved cited work.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:56.082065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:56.082065Z digest=sha256:c1b56e7ff6635a49b4f6c4a57698d45d0b85b1391642890566f08fa8fda98cd8

Observation 58b4c4e0-f525-4b39-a15a-1f80447ad69c · outbound

This paper cites Generate rather than Retrieve: Large Language Models are Strong Context Generators.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis Generate rather than Retrieve: Large Language Models are Strong Context Generators

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:56.152073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:56.152073Z digest=sha256:eecc8c41bf86758e0fc99d79b6838e88cd81ca7c36b92425a60453fca7c4986b

Observation da3a6cc5-e9a5-451f-8805-ee1d4d2b3719 · outbound

This paper cites RAFT: Adapting Language Model to Domain Specific RAG.

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis RAFT: Adapting Language Model to Domain Specific RAG

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:30:56.248436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:30:56.248436Z digest=sha256:b3fc02ec73ac8c8cc7cb3a40c9f12d553cfe3cd4d89aa4233bf3224007142a08

Pith citing papers

No inbound Pith citation observations are available.