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Paper Citation Record · LEDGER

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2502.05431.

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

pith.paper-citation-record.v1
2502.05431 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:28:43.759802Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:31:36.983054Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:43:12.641152Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved33
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a0551778-4d7a-4fdf-be07-a7609cbc3cec · outbound

This paper cites GPT-4 Technical Report.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-08T19:28:43.306048Z digest=sha256:ed734fd7eeae90e51f52630b02b013b2b5e5cc28bd439840f0e74f7ab4c38793

Observation 902a225d-5e90-4a2d-bdd7-a26461ddc749 · outbound

This paper cites LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

Reference 4

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source=pdf_text observed=2026-08-08T19:28:43.322808Z digest=sha256:d2e0dacdadad132d660ec110711410f5b2bb2c093c6b1bfc80348f2f536397df

Observation 113438f2-eed1-4eae-998e-69c94f897aa6 · outbound

This paper cites Memory Transformer.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Memory Transformer

Reference 5

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source=pdf_text observed=2026-08-08T19:28:43.328174Z digest=sha256:ee9675ded2b39bfb92cea3df925e5ef6e6cdf5d1a709965d50aff7511f7aa99e

Observation 474603cd-cc3e-4626-bf23-1319be869baf · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Training Verifiers to Solve Math Word Problems

Reference 7

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source=pdf_text observed=2026-08-08T19:28:43.338271Z digest=sha256:d67b530b1b4c6e96548595b341f5693322f5949edea52216892e3e7962d46942

Observation 3aad025f-6a2a-474a-aa6c-a7ccd4d0567e · outbound

This paper cites Mention Memory: incorporating textual knowledge into Transformers through entity mention attention.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Mention Memory: incorporating textual knowledge into Transformers through entity mention attention

Reference 8

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verified exact
local_arxiv, observed 2026-08-08T19:28:44.326383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T19:28:43.343711Z digest=sha256:0411abd6d41b4ecd7843ec6ddfc81305ad54fb976674d6ffc52d1806cb8d8636

Observation 2726cdda-454e-41ab-a5e3-d1a8d808215c · outbound

This paper cites The Faiss library.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding The Faiss library

Reference 11

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source=pdf_text observed=2026-08-08T19:28:43.364548Z digest=sha256:4196c354720603a08a59f264480753b6b889f502ee6035cb78dc2d190e045b92

Observation 75e7f1b8-3fa2-40d8-a19f-395173e4b988 · outbound

This paper cites The Llama 3 Herd of Models.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding The Llama 3 Herd of Models

Reference 12

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source=pdf_text observed=2026-08-08T19:28:43.394772Z digest=sha256:685b1b390e4f96e26d366e5f5364d63e67aae5d14ffb9d2533c8b3103d07c187

Observation 056f7750-464e-44f8-bb30-fb714f4812d9 · outbound

This paper cites Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model

Reference 13

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source=pdf_text observed=2026-08-08T19:28:43.420237Z digest=sha256:74af3bd360b1da2aed335d8c50f4cfc259fb9e69b8e10c9ee3584522e8cb60a5

Observation 8fe56828-d11b-493f-8e9c-9c254f4da02f · outbound

This paper cites Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang

Reference 15

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source=pdf_text observed=2026-08-08T19:28:43.431194Z digest=sha256:22f219e321af43092ba75598b7029b5cbadc7995a0744a4886c9eab110ae2307

Observation 15e398b9-1767-4aad-a10d-23fb85fb751e · outbound

This paper cites RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

Reference 16

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source=pdf_text observed=2026-08-08T19:28:43.436028Z digest=sha256:07b28279a835b8731558c5d3dc19eb6f46ee889972497be326b15bc92df7c7b5

Observation 645247e7-a812-472a-b220-6f9b792e2cb3 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Measuring Massive Multitask Language Understanding

Reference 17

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source=pdf_text observed=2026-08-08T19:28:43.440664Z digest=sha256:354b8ca59cc87f29eb71761c4975c21465746ffe754ef0f245dfcd808eee828e

Observation 83ebd8ad-f31d-47dd-876e-b09ce0f4d810 · outbound

This paper cites Mistral 7B.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Mistral 7B

Reference 19

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source=pdf_text observed=2026-08-08T19:28:43.450475Z digest=sha256:3950d6cb70e81cf6bd4ed537ede7ef810b1b40ae81ce9afaab225d89286c2c6e

Observation 869c4170-945e-4fed-824b-5686e7ea904b · outbound

This paper cites MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 20

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source=pdf_text observed=2026-08-08T19:28:43.455099Z digest=sha256:4657ace8462756f089d9e0f85225968d6d43fa1d53a00a3dbce27aafe51f2962

Observation 64922e7d-6c64-4904-a360-28e1d92e09be · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 21

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source=pdf_text observed=2026-08-08T19:28:43.459763Z digest=sha256:0153a1fd33f42e97cdaf95305472d7604ea33a17232f880ba1b5408167672dd7

Observation b961bae0-5992-4ce4-acbb-c474c54d87db · outbound

This paper cites Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?

Reference 22

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source=pdf_text observed=2026-08-08T19:28:43.472132Z digest=sha256:372d4671031311c15f675fb3376d0abba751f45e0bdc45aee78b97f0f0e18763

Observation 0031ee46-c419-4e2f-a871-ac858000664f · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 23

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source=pdf_text observed=2026-08-08T19:28:43.517331Z digest=sha256:ca19b26f5e837b77b037c352366d9c18caf63074eb3a5baf3aae52f670e6165e

Observation 34fe0776-94ca-4ed2-ba5f-a712a68bc9fa · outbound

This paper cites FocusLLM: Precise Understanding of Long Context by Dynamic Condensing.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding FocusLLM: Precise Understanding of Long Context by Dynamic Condensing

Reference 24

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source=pdf_text observed=2026-08-08T19:28:43.569455Z digest=sha256:fc8e57290b26ac5bf1221117064db5c89b234c01d7abbcc83857baaf5d3fc48b

Observation 39a663c5-0200-42f1-856a-ae6d7ff071d7 · outbound

This paper cites LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Reference 25

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source=pdf_text observed=2026-08-08T19:28:43.581431Z digest=sha256:f9c14fcfc03aed2c04ea8f471717056ce15c0c2c7a04002793de51406c6fe362

Observation 7aac8b85-0e6b-4fa0-a156-9f2ed6427d74 · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 26

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source=pdf_text observed=2026-08-08T19:28:43.586788Z digest=sha256:c7e20afbf2838d7065e6b25d0bcfbebe822a06f9b7a4d608d722c97dd741e8f3

Observation ca803020-9500-4a76-be64-425cfb1eb168 · outbound

This paper cites Parallel Context Windows for Large Language Models.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Parallel Context Windows for Large Language Models

Reference 27

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source=pdf_text observed=2026-08-08T19:28:43.591899Z digest=sha256:2378dead64bbe32c51d08dc962864b2b773313202b7767830674bcc89eccb4f5

Observation 6fdb970b-33dd-4543-bf71-6990a9779315 · outbound

This paper cites Block-Attention for Efficient Prefilling.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Block-Attention for Efficient Prefilling

Reference 28

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source=pdf_text observed=2026-08-08T19:28:43.596934Z digest=sha256:bc90b25de2a2e72ec7db3c52c21c6e161fd645590ba2ea73dd84f074319f2784

Observation f1464f1d-834b-42ec-84ee-843dc87b1a08 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Gemma 2: Improving Open Language Models at a Practical Size

Reference 29

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source=pdf_text observed=2026-08-08T19:28:43.601752Z digest=sha256:e5b18eefd814f0f039d538e60b5120404ba37ebd62a5a107aeb1c1ce85c6cecc

Observation caf6f47e-ce7d-42bf-86a5-364f1ed8d147 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Efficient Streaming Language Models with Attention Sinks

Reference 31

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source=pdf_text observed=2026-08-08T19:28:43.612246Z digest=sha256:d2495b6c96452172a205231a9b6f269b6acc355d004a9594e21027549da835c3

Observation b01b69e4-0a6b-49d4-833d-391e8b0a428a · outbound

This paper cites CRAG -- Comprehensive RAG Benchmark.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding CRAG -- Comprehensive RAG Benchmark

Reference 32

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source=pdf_text observed=2026-08-08T19:28:43.617686Z digest=sha256:e25caa129dea6dd69b887ab03f46b9cd40b83bc7e0b74a9d63611eeba293a220

Observation 6a74cab3-07f0-461e-aea1-95a742dfcdf5 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 33

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source=pdf_text observed=2026-08-08T19:28:43.651666Z digest=sha256:8c2db03ecc2ac75aa95bf2514e6a1b2f92ba00eea07b7a224961a7f02bea9c05

Observation 0888372b-f2a0-4b83-b354-c61d8b0fa1d6 · outbound

This paper cites Long-Context Language Modeling with Parallel Context Encoding.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Long-Context Language Modeling with Parallel Context Encoding

Reference 34

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source=pdf_text observed=2026-08-08T19:28:43.720166Z digest=sha256:2280c99c6d19b79e3c200eefa1268c0379a5191817cd6f1cd039a76a8ad9cce8

Observation a73a56d5-7680-4e47-af8e-d98de4528697 · outbound

This paper cites Qdrant, 2024.https://qdrant.tech/.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Qdrant, 2024.https://qdrant.tech/

Reference 35

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raw_fallback, observed 2026-08-08T19:28:44.497879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T19:28:43.747887Z digest=sha256:cec7a35eda8674dac76dd67f1e1d33eac94ffefcfac916dac15b633f21aa749f

Observation b3d416ec-ca69-43ad-abbf-c0a8d6f626e0 · outbound

This paper cites (2017), and MMLU (Hendrycks et al., 2020b).

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding (2017), and MMLU (Hendrycks et al., 2020b)

Reference 36

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raw_fallback, observed 2026-08-08T19:28:44.482139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T19:28:43.753881Z digest=sha256:b565f116ab7156f02c3cc2fca2b652295f8d8758a487c1c0f5432fd20a8d7b76

Observation e31b7ed3-fc7a-4017-b4c9-d55e500776be · outbound

This paper cites an unresolved cited work.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-08T19:28:44.465521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T19:28:43.759802Z digest=sha256:5a786033dd01dd9546e85c46d864b337ab0debd0d803d3a92701107cfc5132b0

Observation 11627c03-34dc-489f-9262-f71ecc3c307f · outbound

This paper cites Emergent Abilities of Large Language Models.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Emergent Abilities of Large Language Models

Reference 2017

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source=pdf_text observed=2026-08-08T19:28:43.606824Z digest=sha256:31fbdc4b4efd91948f22603d91fa2441af8c70678c6b6611f493bc68cbeaba1d

Observation 124afffb-51fa-4940-97fc-bc32e31eebbb · outbound

This paper cites A Survey on In-context Learning.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding A Survey on In-context Learning

Reference 2018

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source=pdf_text observed=2026-08-08T19:28:43.353389Z digest=sha256:d33ec44164be52fb523027cdda07a92cb2aeaec03fa72ec7f84f05ea1227f459

Observation 8763abe9-b4b2-4851-b077-692a257ca601 · outbound

This paper cites Entities as Experts: Sparse Memory Access with Entity Supervision.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Entities as Experts: Sparse Memory Access with Entity Supervision

Reference 2019

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source=pdf_text observed=2026-08-08T19:28:43.425662Z digest=sha256:b60f8e3ba96f9d76555aded4c77d9266c8f4193c5e425d81d5dc3e0a6cc09d7c

Observation 5017cef2-2a3e-4be4-a74b-fcf3063ad37e · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 2020

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source=pdf_text observed=2026-08-08T19:28:43.445641Z digest=sha256:4ce9a930063f3bb54278941b3fb987eb1e35523b46099e970778a70dfcc47057

Observation bae0c3c1-7a69-4e91-998e-f7c67bc63267 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2021

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source=pdf_text observed=2026-08-08T19:28:43.348345Z digest=sha256:aa0af20aab8dd45acf7be682c8c97d7dc45f829eefc79e29713b6a6698588f22

Observation c7e440b4-8fcc-4f36-af4f-daa8441009f6 · outbound

This paper cites Extending Context Window of Large Language Models via Positional Interpolation.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Extending Context Window of Large Language Models via Positional Interpolation

Reference 2022

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source=pdf_text observed=2026-08-08T19:28:43.333199Z digest=sha256:fcd0e97c3e02fd886db964333216169ebf64f36036683e8d06fd5b093b0299bc

Observation 7c28b9c9-f8ff-4321-b2c4-bc0b18b67475 · outbound

This paper cites Many-Shot In-Context Learning.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Many-Shot In-Context Learning

Reference 2023

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source=pdf_text observed=2026-08-08T19:28:43.311989Z digest=sha256:ad1353245d2c3424027543f9fb4901e03123a39f23b4f4023d13b32da5b4c39f

Observation 4d8f61f1-50a2-41a9-9d63-d87e6fc236c7 · outbound

This paper cites Reliable, Adaptable, and Attributable Language Models with Retrieval.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding Reliable, Adaptable, and Attributable Language Models with Retrieval

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-08T19:28:43.317352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:28:43.317352Z digest=sha256:bbb0f06496748aa4eac11f25581e274b2bcb90fe030b8af60a8b50cdc2a93e7c

Pith citing papers

Observation af58e0d0-8ce4-44b2-bf49-48ae2336df7b · inbound

Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation cites this paper.

Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T22:31:36.983054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:31:36.983054Z digest=sha256:73dfe5ee555404423351707b611ae9c3bd78ecdcb1d7b54a71fe570455fd6055

Observation 90369c9d-5bf3-4330-8ee0-e8d51e65541c · inbound

Context Memorization for Efficient Long Context Generation cites this paper.

Context Memorization for Efficient Long Context Generation APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:43:12.642761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T10:39:09.720412Z digest=sha256:a5405d52d3643e3d86b5d5c9fab8647566ce2ea1a844e3bfa90d0837a9843539