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Paper Citation Record · LEDGER

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems

As of 20 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2608.08237.

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

pith.paper-citation-record.v1
2608.08237 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:18:13.999584Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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External citation measurements

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Outbound references

Observation f29a7b35-64cb-4397-bb76-607e9e6921c2 · outbound

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

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 1

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Observation b369b6d4-613b-4e52-8052-7a5301d5ba3d · outbound

This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems REALM: Retrieval-Augmented Language Model Pre-Training

Reference 2

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source=pdf_text observed=2026-08-12T00:18:13.876311Z digest=sha256:f6901b688bac7f6ca297135edac1580aef28a4f97eab2f9819056af6596e32a1

Observation 3b92f5a3-2715-4f8c-83a4-ff4f11b70992 · outbound

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

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Dense Passage Retrieval for Open-Domain Question Answering

Reference 3

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source=pdf_text observed=2026-08-12T00:18:13.882507Z digest=sha256:8c5783211a674fa06ed061438f84aecbaf6fcb702d7a28ad086f5a6af309377f

Observation f66e66a1-c4af-422f-ba29-6358f68249af · outbound

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

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 4

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source=pdf_text observed=2026-08-12T00:18:13.888120Z digest=sha256:05eaf4a4fb42fbb7e365dc6905cde98faffa7246c0be368f3ea36f3f22be431c

Observation 30e185e3-6d79-4ae6-ad9b-232d6ea032f8 · outbound

This paper cites The tail at scale,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems The tail at scale,

Reference 5

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source=pdf_text observed=2026-08-12T00:18:13.893649Z digest=sha256:059a6cf4c0cbfc2d438b592ea0d7a71a1fc0599abedbadd06c637f224f8838e8

Observation 33b734c3-39f4-4692-98aa-900d38c32715 · outbound

This paper cites Active Retrieval Augmented Generation.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Active Retrieval Augmented Generation

Reference 6

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Observation f4160962-200c-488c-a76c-a27488aab3f8 · outbound

This paper cites Self-RAG: Learning to retrieve, generate, and critique through self-reflection,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Self-RAG: Learning to retrieve, generate, and critique through self-reflection,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b6708ed6-1879-4ac3-a36b-ebf6ffa49111 · outbound

This paper cites Efficient context selection for long-context qa: No tuning, no iteration, just adaptive- k,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Efficient context selection for long-context qa: No tuning, no iteration, just adaptive- k,

Reference 8

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 19ebdd6f-3e4f-4f18-aae5-c1193df9b17e · outbound

This paper cites Stop-RAG: Value-based retrieval control for iterative rag,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Stop-RAG: Value-based retrieval control for iterative rag,

Reference 9

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Observation ba4f8f8a-f4ea-4a4c-ba3b-7153e8c19f4d · outbound

This paper cites Leveraging passage retrieval with generative models for open domain question answering,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Leveraging passage retrieval with generative models for open domain question answering,

Reference 10

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Observation e291a53a-3ce9-4be7-a030-176c73ac459d · outbound

This paper cites FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference

Reference 11

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Observation 0f56cb21-86e2-41e0-9c94-3bf8b6a3449e · outbound

This paper cites The probabilistic relevance framework: BM25 and beyond,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems The probabilistic relevance framework: BM25 and beyond,

Reference 12

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source=pdf_text observed=2026-08-12T00:18:13.929080Z digest=sha256:a31ed3e27d606827a7c95d742b0f448aa9739110eb962e1f81c22115c8b32ef8

Observation bfc58a1a-70c1-40b3-8aa3-03648c40cdf8 · outbound

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

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Reciprocal rank fusion outperforms condorcet and individual rank learning methods,

Reference 13

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source=pdf_text observed=2026-08-12T00:18:13.934075Z digest=sha256:01be0b3fb6620cb074e5b6dc9d0689d6ab060d2f8719bb3a60106b30b79f1742

Observation 6b8669d0-03d8-440a-8e48-251c69c58536 · outbound

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

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 14

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Observation 1b6de2f5-6d9e-4b3e-969b-1c489adb30a8 · outbound

This paper cites DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models

Reference 15

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Observation 7151b7c7-ba80-4cad-90ef-cf0ba69d8996 · outbound

This paper cites Seakr: Self-aware knowledge retrieval for adaptive retrieval augmented generation,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Seakr: Self-aware knowledge retrieval for adaptive retrieval augmented generation,

Reference 16

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Observation 86bc9727-599b-4343-b6f0-c752fa399b86 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Efficient memory management for large language model serving with pagedattention,

Reference 17

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Observation af4554ba-9510-4381-b6ff-f1f37237ca3d · outbound

This paper cites Slo-power: SLO and power- aware elastic scaling for web services,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Slo-power: SLO and power- aware elastic scaling for web services,

Reference 18

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Observation 16ec2df0-a163-43ee-baa5-6523f072b14a · outbound

This paper cites JITServe: SLO-aware LLM serving with imprecise request information,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems JITServe: SLO-aware LLM serving with imprecise request information,

Reference 19

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Observation f9b8519f-cd69-4ac3-a3ec-0c6f492c14b0 · outbound

This paper cites A reduction of imitation learning and structured prediction to no-regret online learning,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems A reduction of imitation learning and structured prediction to no-regret online learning,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c855194b-e30b-43ae-b57d-756dcf80b9de · outbound

This paper cites Imitation learning: A survey of learning methods,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Imitation learning: A survey of learning methods,

Reference 21

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Observation baa7fd98-b102-4c1f-9d78-1f77574ada0e · outbound

This paper cites Natural questions: A benchmark for question answering research,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Natural questions: A benchmark for question answering research,

Reference 22

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Observation c6195c21-8d53-4238-8efe-0fff6b9c8fdd · outbound

This paper cites HOTPOTQA: A dataset for diverse, explainable multi-hop question answering,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems HOTPOTQA: A dataset for diverse, explainable multi-hop question answering,

Reference 23

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Observation 994885ea-f9bc-4ebc-b1a2-7538edc703a7 · outbound

This paper cites UnSeenTimeQA: Time-sensitive Question-Answering beyond LLMs’ Memorization,.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems UnSeenTimeQA: Time-sensitive Question-Answering beyond LLMs’ Memorization,

Reference 24

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Observation 696c184d-8543-40db-baac-23a5a670605c · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 25

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Observation 9a553cfd-4362-47b1-add6-1a974ef93364 · outbound

This paper cites Available: https://doi.org/10.48550/arXiv.2504.20068.

SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems Available: https://doi.org/10.48550/arXiv.2504.20068

Reference 2025

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doi, observed 2026-08-12T00:18:14.215641Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

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