Paper Citation Record · LEDGER

Multiple Abstraction Level Retrieve Augment Generation

As of 10 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 1 inbound Pith citation observation for arXiv:2501.16952.

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

pith.paper-citation-record.v1
2501.16952 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:33:52.528776Z

measured 70 of 70 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T07:01:03.093718Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:38:28.935706Z

Reference resolution

69 of 69 outbound references displayed

verified exact3
verified fuzzy15
unresolved51
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1709d0bf-08d5-4dfe-adc3-12ae6c3b3b01 · outbound

This paper cites Generative AI Text Classification using Ensemble LLM Approaches.

Multiple Abstraction Level Retrieve Augment Generation Generative AI Text Classification using Ensemble LLM Approaches

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.213794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30e33b65-f72f-4b49-81ac-065eca7c35c8 · outbound

This paper cites Improving language models by retrieving from trillions of tokens.

Multiple Abstraction Level Retrieve Augment Generation Improving language models by retrieving from trillions of tokens

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.902985Z

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.

Observation d0390e66-044b-480f-96a1-96f7f39f5a5a · outbound

This paper cites Dense X Retrieval: What Retrieval Granularity Should We Use?.

Multiple Abstraction Level Retrieve Augment Generation Dense X Retrieval: What Retrieval Granularity Should We Use?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.249970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba104950-6a9f-493a-acc3-54432af5ede8 · outbound

This paper cites HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA.

Multiple Abstraction Level Retrieve Augment Generation HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.254582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e92c2382-0692-4f25-b4b1-74f2f695e750 · outbound

This paper cites Enhancing ai-assisted group decision making through llm-powered devil’s advocate.

Multiple Abstraction Level Retrieve Augment Generation Enhancing ai-assisted group decision making through llm-powered devil’s advocate

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.888182Z

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.

Observation 7a3a0e30-6fce-49cc-9a44-059895ffd86e · outbound

This paper cites Evaluation of question-answering based text summarization using llm invited paper.

Multiple Abstraction Level Retrieve Augment Generation Evaluation of question-answering based text summarization using llm invited paper

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.873177Z

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.

Observation 21df1cc1-fa31-43d0-9d80-41fe6d4c84e3 · outbound

This paper cites Improving LLM Abilities in Idiomatic Translation.

Multiple Abstraction Level Retrieve Augment Generation Improving LLM Abilities in Idiomatic Translation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.268221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 690c1782-53e7-41c7-988e-fd189b6a92ea · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Multiple Abstraction Level Retrieve Augment Generation From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.273205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36cadd33-3d34-4c37-b269-f74425cbc75b · outbound

This paper cites Determinants of LLM-assisted Decision-Making.

Multiple Abstraction Level Retrieve Augment Generation Determinants of LLM-assisted Decision-Making

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.278088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 971d1020-2159-4481-9b6f-6778f45ab1fd · outbound

This paper cites From general llm to translation: How we dramatically improve transla- tion quality using human evaluation data for llm finetun- ing.

Multiple Abstraction Level Retrieve Augment Generation From general llm to translation: How we dramatically improve transla- tion quality using human evaluation data for llm finetun- ing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.857004Z

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.

Observation 936e3f70-3737-4483-9666-fb5292f81355 · outbound

This paper cites "You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representation.

Multiple Abstraction Level Retrieve Augment Generation "You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representation

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-10T05:33:53.488697Z

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.

Observation 65590f97-a987-4c35-8885-56bc15654dca · outbound

This paper cites Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration.

Multiple Abstraction Level Retrieve Augment Generation Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.292108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e6f9ada-2cd5-456a-942f-afd0eada5adf · outbound

This paper cites Precise Zero-Shot Dense Retrieval without Relevance Labels.

Multiple Abstraction Level Retrieve Augment Generation Precise Zero-Shot Dense Retrieval without Relevance Labels

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.296920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80d08438-f232-4a01-9486-425c1f1dbd8c · outbound

This paper cites Enabling Large Language Models to Generate Text with Citations.

Multiple Abstraction Level Retrieve Augment Generation Enabling Large Language Models to Generate Text with Citations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.302231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc9ab8df-228a-44f3-826d-e093ae50ed11 · outbound

This paper cites Harnessing the power of metadata for enhanced question retrieval in community question answering.IEEE Access, 12:65768–65779,.

Multiple Abstraction Level Retrieve Augment Generation Harnessing the power of metadata for enhanced question retrieval in community question answering.IEEE Access, 12:65768–65779,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.842171Z

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.

Observation 9e70051f-dca8-458a-a2cc-745fa7c3aedb · outbound

This paper cites Re2G: Retrieve, Rerank, Generate.

Multiple Abstraction Level Retrieve Augment Generation Re2G: Retrieve, Rerank, Generate

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.312061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0aaa2147-f504-4e25-bfe2-5719eda605aa · outbound

This paper cites Retrieval aug- mented language model pre-training.

Multiple Abstraction Level Retrieve Augment Generation Retrieval aug- mented language model pre-training

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.828251Z

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.

Observation 918c7b1d-c37f-4db1-bfb4-aa33f9dba24f · outbound

This paper cites Metadata-based Data Exploration with Retrieval-Augmented Generation for Large Language Models.

Multiple Abstraction Level Retrieve Augment Generation Metadata-based Data Exploration with Retrieval-Augmented Generation for Large Language Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-10T05:33:53.409189Z

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.

Observation b0d79929-4cf8-46ba-849a-3fe39b862806 · outbound

This paper cites A survey on hallucination in large language models: Prin- ciples, taxonomy, challenges, and open questions.

Multiple Abstraction Level Retrieve Augment Generation A survey on hallucination in large language models: Prin- ciples, taxonomy, challenges, and open questions

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.812858Z

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.

Observation 32e361da-ad44-4885-aa8e-d7c67225a730 · outbound

This paper cites A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industry.

Multiple Abstraction Level Retrieve Augment Generation A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industry

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.329866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3518522a-dcad-4630-ae68-dbad6649dc46 · outbound

This paper cites DSLR: Document Refinement with Sentence-Level Re-ranking and Reconstruction to Enhance Retrieval-Augmented Generation.

Multiple Abstraction Level Retrieve Augment Generation DSLR: Document Refinement with Sentence-Level Re-ranking and Reconstruction to Enhance Retrieval-Augmented Generation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.333732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a368884-86dd-43fa-beb9-6f23102b7edb · outbound

This paper cites Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering.

Multiple Abstraction Level Retrieve Augment Generation Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.337934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb094c91-729d-4caa-bd27-e2c87d2ea9a7 · outbound

This paper cites TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems.

Multiple Abstraction Level Retrieve Augment Generation TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.341822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef579b17-11d1-4415-8235-095688f9df78 · outbound

This paper cites Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG.

Multiple Abstraction Level Retrieve Augment Generation Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.346459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0384e5e9-126e-419c-8ad4-06a7b494405a · outbound

This paper cites A comprehensive sur- vey on process-oriented automatic text summarization with exploration of llm-based methods.

Multiple Abstraction Level Retrieve Augment Generation A comprehensive sur- vey on process-oriented automatic text summarization with exploration of llm-based methods

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.351610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09723710-721f-4279-a6fd-5da1a8faab23 · outbound

This paper cites LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning.

Multiple Abstraction Level Retrieve Augment Generation LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.356340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b8753e2-e0fd-4d2e-af53-217b80db3545 · outbound

This paper cites Generalization through Memorization: Nearest Neighbor Language Models.

Multiple Abstraction Level Retrieve Augment Generation Generalization through Memorization: Nearest Neighbor Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.361486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72be3775-cbf8-4836-bc3e-2448d7efeddf · outbound

This paper cites TransLLaMa: LLM-based Simultaneous Translation System.

Multiple Abstraction Level Retrieve Augment Generation TransLLaMa: LLM-based Simultaneous Translation System

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.370487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff80939-deca-48a1-972e-db078b4f5232 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Multiple Abstraction Level Retrieve Augment Generation Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.375213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e7d81ec-4857-4f49-9935-89866ecf1803 · outbound

This paper cites DMQR-RAG: Diverse Multi-Query Rewriting for RAG.

Multiple Abstraction Level Retrieve Augment Generation DMQR-RAG: Diverse Multi-Query Rewriting for RAG

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.379391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41107a4-8c17-4b84-8c35-4277f458ee3a · outbound

This paper cites Revolutionizing Retrieval-Augmented Generation with Enhanced PDF Structure Recognition.

Multiple Abstraction Level Retrieve Augment Generation Revolutionizing Retrieval-Augmented Generation with Enhanced PDF Structure Recognition

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.384381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc5f11bb-c20b-43d5-b607-511df525dc33 · outbound

This paper cites Multi- modal molecule structure–text model for text-based re- trieval and editing.

Multiple Abstraction Level Retrieve Augment Generation Multi- modal molecule structure–text model for text-based re- trieval and editing

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.773020Z

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.

Observation 55cdf41f-c2a0-4d6e-91c7-dd09b63c1cb7 · outbound

This paper cites Lost in the middle: How language mod- els use long contexts.

Multiple Abstraction Level Retrieve Augment Generation Lost in the middle: How language mod- els use long contexts

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.758272Z

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.

Observation f82ef462-85f6-4f26-8899-5581155e694c · outbound

This paper cites an unresolved cited work.

Multiple Abstraction Level Retrieve Augment Generation Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-10T05:33:53.743217Z

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.

Observation 425b7748-d9f2-47e0-a2a3-561e716746c2 · outbound

This paper cites Query Rewriting for Retrieval-Augmented Large Language Models.

Multiple Abstraction Level Retrieve Augment Generation Query Rewriting for Retrieval-Augmented Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.402598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46a34667-df65-4aaf-80a1-9b6f41a292c1 · outbound

This paper cites RaFe: Ranking Feedback Improves Query Rewriting for RAG.

Multiple Abstraction Level Retrieve Augment Generation RaFe: Ranking Feedback Improves Query Rewriting for RAG

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.407098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88b75e48-b10d-41f0-bb67-66e1ad2199cf · outbound

This paper cites AmbigQA: Answering Ambiguous Open-domain Questions.

Multiple Abstraction Level Retrieve Augment Generation AmbigQA: Answering Ambiguous Open-domain Questions

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.411138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 660b9a46-7230-4213-b671-9c7df1058bc6 · outbound

This paper cites Searchd-advanced retrieval with text generation using large language models and cross encoding re-ranking.

Multiple Abstraction Level Retrieve Augment Generation Searchd-advanced retrieval with text generation using large language models and cross encoding re-ranking

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.727201Z

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.

Observation be790276-9984-4c5e-a405-1fd2c5d3d42f · outbound

This paper cites DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs.

Multiple Abstraction Level Retrieve Augment Generation DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.418936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef99a386-9e0a-42c8-bbef-181250cfa83a · outbound

This paper cites A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges.

Multiple Abstraction Level Retrieve Augment Generation A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.423594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77948597-9ab7-4152-991c-acbb4d0f6b72 · outbound

This paper cites An Empirical Study of the Non-determinism of ChatGPT in Code Generation.

Multiple Abstraction Level Retrieve Augment Generation An Empirical Study of the Non-determinism of ChatGPT in Code Generation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.428134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcf0064e-803b-4250-a5b4-1f135d6b71d1 · outbound

This paper cites Large language model based long-tail query rewriting in taobao search.

Multiple Abstraction Level Retrieve Augment Generation Large language model based long-tail query rewriting in taobao search

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.712551Z

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.

Observation aab7c1fd-d54d-4ad2-9fe8-1dc091f129b0 · outbound

This paper cites Summarization is (Almost) Dead.

Multiple Abstraction Level Retrieve Augment Generation Summarization is (Almost) Dead

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.437416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50d44add-04bd-43a1-bd48-fe12f6f92c38 · outbound

This paper cites Maximizing rag efficiency: A comparative analysis of rag methods.

Multiple Abstraction Level Retrieve Augment Generation Maximizing rag efficiency: A comparative analysis of rag methods

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.696559Z

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.

Observation 94bcb6b9-8973-4f9b-a553-44b4aeb745a9 · outbound

This paper cites RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval.

Multiple Abstraction Level Retrieve Augment Generation RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.446520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0d07771-579d-4179-a209-9ddd5f1d6052 · outbound

This paper cites Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems.

Multiple Abstraction Level Retrieve Augment Generation Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-10T05:33:52.792207Z

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.

Observation c3f80d72-81a3-428f-9c93-8616607313c2 · outbound

This paper cites SciRepEval: A Multi-Format Benchmark for Scientific Document Representations.

Multiple Abstraction Level Retrieve Augment Generation SciRepEval: A Multi-Format Benchmark for Scientific Document Representations

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.455784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be69f80b-b14b-458a-bab7-6fe03d2ca42a · outbound

This paper cites GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning.

Multiple Abstraction Level Retrieve Augment Generation GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.460630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc7a697-0ce3-4691-9ebc-60b3daa5fd7b · outbound

This paper cites SynCode: LLM Generation with Grammar Augmentation.

Multiple Abstraction Level Retrieve Augment Generation SynCode: LLM Generation with Grammar Augmentation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.465213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6691fb-a26d-4406-8145-f60050d60ee3 · outbound

This paper cites Retrieval-based Controllable Molecule Generation.

Multiple Abstraction Level Retrieve Augment Generation Retrieval-based Controllable Molecule Generation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.469687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7221693b-2aae-468e-96dc-8bd017701f07 · outbound

This paper cites BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs.

Multiple Abstraction Level Retrieve Augment Generation BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.474042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fe5f1ba-bb8f-47c9-b9f6-d1b1b02fb05f · outbound

This paper cites BioRAG: A RAG-LLM Framework for Biological Question Reasoning.

Multiple Abstraction Level Retrieve Augment Generation BioRAG: A RAG-LLM Framework for Biological Question Reasoning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.478582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b1d2930-17f2-4325-b90b-8da14cd5b3b1 · outbound

This paper cites Recursively Summarizing Books with Human Feedback.

Multiple Abstraction Level Retrieve Augment Generation Recursively Summarizing Books with Human Feedback

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.483825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcbe6cb5-4549-4f6e-9635-3ce62ea53f31 · outbound

This paper cites Large language models for automated q&a involving legal documents: a survey on algorithms, frameworks and applications.

Multiple Abstraction Level Retrieve Augment Generation Large language models for automated q&a involving legal documents: a survey on algorithms, frameworks and applications

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.666519Z

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.

Observation b63c64ad-4049-4f7d-9c78-d6026289ef7d · outbound

This paper cites Financial Report Chunking for Effective Retrieval Augmented Generation.

Multiple Abstraction Level Retrieve Augment Generation Financial Report Chunking for Effective Retrieval Augmented Generation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.497240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fead3cac-97ab-4397-bb1f-1c268155f0ac · outbound

This paper cites How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances.

Multiple Abstraction Level Retrieve Augment Generation How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.501750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28723bcd-8641-47dc-adeb-842f01b52151 · outbound

This paper cites Long Context Compression with Activation Beacon.

Multiple Abstraction Level Retrieve Augment Generation Long Context Compression with Activation Beacon

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.505754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ba4344d-9c74-4e7c-b117-2bc2aefdc4eb · outbound

This paper cites Pushing The Limit of LLM Capacity for Text Classification.

Multiple Abstraction Level Retrieve Augment Generation Pushing The Limit of LLM Capacity for Text Classification

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.510468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92be2e07-8814-4e7a-bd9e-80318d1abdc1 · outbound

This paper cites TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision.

Multiple Abstraction Level Retrieve Augment Generation TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.514880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2a224eb-9041-4c00-bc7d-7c3a0ff81834 · outbound

This paper cites LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering.

Multiple Abstraction Level Retrieve Augment Generation LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.519691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 697385d1-91d0-4b8d-993c-cc13f9e72544 · outbound

This paper cites Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.

Multiple Abstraction Level Retrieve Augment Generation Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.524250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d701e6-6864-4a24-bb5c-c993591e3e4b · outbound

This paper cites Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation.

Multiple Abstraction Level Retrieve Augment Generation Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.528776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddd5a0be-4be4-4ef8-81e1-903f1a9bb1d5 · outbound

This paper cites LongAlign: A Recipe for Long Context Alignment of Large Language Models.

Multiple Abstraction Level Retrieve Augment Generation LongAlign: A Recipe for Long Context Alignment of Large Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.229327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e319544-d968-4d32-a9ef-f333fdd8a4c7 · outbound

This paper cites Linq-embed-mistral:elevating text retrieval with improved gpt data through task-specific control and quality refinement.

Multiple Abstraction Level Retrieve Augment Generation Linq-embed-mistral:elevating text retrieval with improved gpt data through task-specific control and quality refinement

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.797750Z

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.

Observation f781d7e7-027d-4920-bb80-82b884a0d04d · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

Multiple Abstraction Level Retrieve Augment Generation RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.245223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd60c65e-a962-4f4b-b68e-77010fb3264d · outbound

This paper cites Prompt-based 3d molecular diffusion models for structure- based drug design.

Multiple Abstraction Level Retrieve Augment Generation Prompt-based 3d molecular diffusion models for structure- based drug design

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:33:53.681666Z

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.

Observation 55ba5661-9ab7-4d77-a4c5-ba276d8ed97e · outbound

This paper cites Language Models are Few-Shot Learners.

Multiple Abstraction Level Retrieve Augment Generation Language Models are Few-Shot Learners

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.239626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e313502-7905-468f-a2c8-84189e975d4d · outbound

This paper cites Large Language Models for Mathematical Reasoning: Progresses and Challenges.

Multiple Abstraction Level Retrieve Augment Generation Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.219126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f4c5b70-9b11-4356-b3d2-faf3f3328553 · outbound

This paper cites Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised.

Multiple Abstraction Level Retrieve Augment Generation Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T05:33:52.224308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8417feab-f6d5-40b9-8655-f03593f5616c · inbound

Uncertainty-Aware Hybrid Retrieval for Long-Document RAG cites this paper.

Uncertainty-Aware Hybrid Retrieval for Long-Document RAG Multiple Abstraction Level Retrieve Augment Generation

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:38:28.937287Z

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.