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Paper Citation Record · LEDGER

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2509.06650.

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

pith.paper-citation-record.v1
2509.06650 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:23:42.243349Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

34 of 34 outbound references displayed

  • verified exact4
  • verified fuzzy3
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69805b29-af73-4d7e-8812-3c47715858af · outbound

This paper cites Bhogal, A.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Bhogal, A

Reference 1

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verified exact
doi, observed 2026-08-04T23:23:42.575264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:39.577776Z digest=sha256:9cfdb7a123e47ea50c43bf25909db791eda71596467026f1cbe111d9c06cf4f1

Observation 9abd6403-e251-4e82-87ad-ecd495aae956 · outbound

This paper cites MoL for LLMs: Dual-Loss Optimization to Enhance Domain Expertise While Preserving General Capabilities.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval MoL for LLMs: Dual-Loss Optimization to Enhance Domain Expertise While Preserving General Capabilities

Reference 2

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source=pdf_text observed=2026-08-04T23:23:39.650901Z digest=sha256:f2295f3a203f17119cf3975efba2d13267d7e54a4590d3843c0ee5b49f57fd2d

Observation 55f03057-14b7-4c3a-9ac9-0cf17fdb4da8 · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 3

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verified exact
doi, observed 2026-08-04T23:23:42.407465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:39.741855Z digest=sha256:d0e213af15d5e1f9f16c566fb8efdb28fd950e4da021b6c061ebd11f0c985b36

Observation 70f294d2-51b9-4567-a07c-054abbee7f50 · outbound

This paper cites Cormack, Charles L A Clarke, and Stefan Buettcher.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Cormack, Charles L A Clarke, and Stefan Buettcher

Reference 4

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no resolver link, observed 2026-08-04T23:23:39.797726Z

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source=pdf_text observed=2026-08-04T23:23:39.797726Z digest=sha256:8f2d15f1aa4ab7ac7b0beb480252274b5ed302d3d6239c022110b79b2b1ea5c2

Observation 81c4203b-a51b-4d64-b50f-231f06dee12f · outbound

This paper cites Continual Pre-Training Mitigates Forgetting in Language and Vision.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Continual Pre-Training Mitigates Forgetting in Language and Vision

Reference 5

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verified exact
local_arxiv, observed 2026-08-04T23:23:43.286600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:39.859749Z digest=sha256:a65b9f6acae6b17e981b03a2f550de1de4d1a4014cfddf97e3e4900b3e1094a3

Observation a0d1ef20-c9f5-442d-8753-abe10987d30b · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:39.956935Z digest=sha256:b58ccbaca62eed75de3256c5ae0786899daf9a549fcf9d6533f86f6501f067c4

Observation 2e16f951-9f7c-470d-813d-8e89f5921112 · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:40.038456Z digest=sha256:82328280aa37297d947b5438c1d57525acbd5f1ee60c8df9817f591daac29535

Observation b4bebb46-5f29-4a1f-8b0e-bb91749ecb03 · outbound

This paper cites ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

Reference 8

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source=pdf_text observed=2026-08-04T23:23:40.126983Z digest=sha256:fa9cb9246b44924e92fc82f0798cd47d62593e8d90fedd1504e0c02a55d869a2

Observation fdc6706f-2a82-41ee-bfe3-9007be5122be · outbound

This paper cites Query Expansion by Prompting Large Language Models.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Query Expansion by Prompting Large Language Models

Reference 9

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source=pdf_text observed=2026-08-04T23:23:40.197978Z digest=sha256:79e0ac5205b64fb7d02a8658a183b4f66ad83ad5ff01c45c97c0bc7e003ef37f

Observation 98afb813-6714-4da2-b86a-1cb88ddd228e · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:40.287539Z digest=sha256:e7d2f7031e99a3be444f3e72d65da65ad70f7e0769dc13c49ee6679622665851

Observation 0a283129-a172-448b-aa20-f26843fd655d · outbound

This paper cites MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion

Reference 11

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source=pdf_text observed=2026-08-04T23:23:40.400761Z digest=sha256:47f193f1a8603297ac8470ea46988bfc8b4bcda57f1014ee36a884d3a8f0d242

Observation d2e0ec60-d36f-407e-9bd4-7b6ae20e19bb · outbound

This paper cites DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Reference 12

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source=pdf_text observed=2026-08-04T23:23:40.444325Z digest=sha256:2603931ff50b8d22b3316c24fe58565297471f1b29e70487290f18cd91e03a78

Observation 4bdab990-9ed0-484a-915f-effcf540beb1 · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:40.515042Z digest=sha256:0a3823ec915d1ebf1f0c3439eec35822fc1e66195de122016f16ecc72a95dc75

Observation 18241805-67db-4464-94b5-3cbe7f472254 · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:40.598797Z digest=sha256:d9871c7298087502c4fe7d14289a1b518e1f2d91d479764a532ffce0f9823a7f

Observation 40d3156f-5c12-4ea6-a62c-bb3569594a8c · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 15

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source=pdf_text observed=2026-08-04T23:23:40.657425Z digest=sha256:a3c27eb41b287a5e9b8e261acdaa8a7fdd651a32b85deffbb7d77c1b4535efd6

Observation 68b05527-681c-4c36-8772-912b3bc89f5b · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:40.724189Z digest=sha256:c72b4fd8e063dea5c33d54892f8cec2d34aab2223918ba658a5337f585bc3af4

Observation ab49911f-d377-4e2e-9369-61d87616415d · outbound

This paper cites 2022.PEFT: State-of-the-art Parameter-Efficient Fine-Tuning Methods.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval 2022.PEFT: State-of-the-art Parameter-Efficient Fine-Tuning Methods

Reference 17

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raw_fallback, observed 2026-08-04T23:23:43.709371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:40.890062Z digest=sha256:eac8503555385103e3727d17ab5f50e70ac545618c08cfcd5a534e649de4ce93

Observation 21ad4ad3-bd77-4e0f-9af8-9b0024aad1dd · outbound

This paper cites Passage Re-ranking with BERT.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Passage Re-ranking with BERT

Reference 18

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source=pdf_text observed=2026-08-04T23:23:40.973515Z digest=sha256:715e0eefce5dece6554783347a02a87558921397d951145808fcb8e6a798a070

Observation d07bbcfa-f8ea-4ea1-9689-b802fba72cae · outbound

This paper cites 2022.New and improved embedding model.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval 2022.New and improved embedding model

Reference 19

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raw_fallback, observed 2026-08-04T23:23:43.477586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:41.076232Z digest=sha256:731882879f942ababd293af610ca180301974702901fb8947dd8b122c56a50a7

Observation 2146f822-66bf-4120-8332-9c3848af6edc · outbound

This paper cites Improving Query Expansion Using WordNet.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Improving Query Expansion Using WordNet

Reference 20

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local_arxiv, observed 2026-08-04T23:23:43.036785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:41.175605Z digest=sha256:71c9fc5b4f2d4959b3c91e3076b733f39e5ab41e3c41575b383d2ddff7ac5399

Observation c97a8514-8870-4127-9d42-c0c82ecb9261 · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-04T23:23:41.268780Z digest=sha256:d8ee876692eb605a9a19515dd3e78fcb55693273036e3bc6a13b378f0332ba8a

Observation 21aebf3f-0839-44f9-91e5-7d6e19226ac6 · outbound

This paper cites ReasonIR: Training Retrievers for Reasoning Tasks.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval ReasonIR: Training Retrievers for Reasoning Tasks

Reference 22

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source=pdf_text observed=2026-08-04T23:23:41.462145Z digest=sha256:43f0278076d2f91ffa120de19192fece7fb3f1e9d23ef676df45e75a8edcd0e5

Observation 09cbdec8-e815-49f7-912e-cedb07a11b06 · outbound

This paper cites How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization

Reference 23

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source=pdf_text observed=2026-08-04T23:23:41.525376Z digest=sha256:00223f616a36a29d4c67caaa97bc0ba0ff353160bfaea89d3b71b8eba63099ce

Observation fd306089-47a6-4ec7-a098-a08a6c526c2c · outbound

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

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 24

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source=pdf_text observed=2026-08-04T23:23:41.597027Z digest=sha256:d190077563b425de8b98f4fbecf9726fd3e475c705970d4d10e41d44cc298f26

Observation d9f1aa58-2b02-46c2-b3c2-10cbb19a23b3 · outbound

This paper cites Query2doc: Query Expansion with Large Language Models.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Query2doc: Query Expansion with Large Language Models

Reference 25

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source=pdf_text observed=2026-08-04T23:23:41.673206Z digest=sha256:3735e830f0a5f7517bed628eb08695fb4eb840b5f8436c32a53fb004beceeccc

Observation e1c883b7-520d-4b4a-97f1-d8b690a827bc · outbound

This paper cites Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond

Reference 26

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source=pdf_text observed=2026-08-04T23:23:41.779153Z digest=sha256:bef7808537a252e9d2a1ccfc51038e48d364ef2cb9eedbb5ce7d086e3f4b6835

Observation dbdc0a48-7af3-4cfa-a9cd-8e15c9f2039d · outbound

This paper cites Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrieval.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrieval

Reference 27

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source=pdf_text observed=2026-08-04T23:23:41.861983Z digest=sha256:d7930ebbfd5c7ac74ebb78abf57995cf015e796d3a67b72d2a2f6de070b29300

Observation a6d2d58f-f8f1-40e5-a3fe-191a8820f608 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval C-Pack: Packed Resources For General Chinese Embeddings

Reference 28

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source=pdf_text observed=2026-08-04T23:23:41.922160Z digest=sha256:593a19d10a1d913d97f4e0589491539763c3d47671b9fb7e852a164ece3a3d80

Observation 7f84c2f7-ed7a-4c3a-ad0b-a9eb6eb8bfea · outbound

This paper cites Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Reference 29

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source=pdf_text observed=2026-08-04T23:23:42.039208Z digest=sha256:153ff4daca2f313db2c7305a2bcccf2d45c40f9e08cd3b72234e876626c0040c

Observation 2f16ca56-a843-4554-ab53-72af1160e194 · outbound

This paper cites Bruce Croft.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Bruce Croft

Reference 30

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arxiv_id, observed 2026-08-04T23:23:42.760503Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:42.092643Z digest=sha256:628d1a2982b2e14462291d05ade78f3ac14b2aa6c54e4216804d0e7a2f28bb4d

Observation 3039e145-d80a-4bf7-aee5-e6288523f38c · outbound

This paper cites Qwen3 Technical Report.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Qwen3 Technical Report

Reference 31

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source=pdf_text observed=2026-08-04T23:23:42.179105Z digest=sha256:85bfbe84be01a2fa6724ce044fcbea839cf91ed92de817d651fefbef0625e67f

Observation a8896a49-5515-412d-9157-a24fc792abab · outbound

This paper cites an unresolved cited work.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Unresolved cited work

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:42.243349Z digest=sha256:84d90aa03d5787a01a44a42b2aa44dae6fa071c3c87cf8e718ff6fe997b4ae42

Observation 2fcb7c2f-6778-477e-94c1-5a1a3de1c925 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval Proximal Policy Optimization Algorithms

Reference 2017

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source=pdf_text observed=2026-08-04T23:23:41.375050Z digest=sha256:3b66c845b0ceff187fc0eec438e71f8fbf8ffcf81614c068efdef128a3afbbe5

Observation c62ebf6c-6ce0-4a80-9ce1-6207c0f4fe00 · outbound

This paper cites https://github.com/sail-sg/understand-r1-zero/blob/main/ understand-r1-zero.pdf Code: https://github.com/sail-sg/understand-r1-zero.

Domain-Aware RAG: MoL-Enhanced RL for Efficient Training and Scalable Retrieval https://github.com/sail-sg/understand-r1-zero/blob/main/ understand-r1-zero.pdf Code: https://github.com/sail-sg/understand-r1-zero

Reference 2025

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verified fuzzy
raw_fallback, observed 2026-08-04T23:23:43.867978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:23:40.822536Z digest=sha256:7bebfd821ab169b79accd82c218588babea510336e5775c174155af0b34d5582

Pith citing papers

No inbound Pith citation observations are available.