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Paper Citation Record · LEDGER

LooGLE: Can Long-Context Language Models Understand Long Contexts?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2311.04939.

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

pith.paper-citation-record.v1
2311.04939 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 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 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:31:43.324780Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:44:41.798978Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6d6c0110-0de0-4372-958d-a2e3decdabb2 · inbound

Evaluating Very Long-Term Conversational Memory of LLM Agents cites this paper.

Evaluating Very Long-Term Conversational Memory of LLM Agents LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 133

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verified exact
arxiv_id, observed 2026-05-12T08:05:12.367090Z

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=arxiv_source observed=2026-05-12T08:05:10.586357Z digest=sha256:5ae65ddd395027ed6d758475c9bb0f5318f2d043ea72d7b263680ef546a33c1e

Observation 707ac0af-f3af-48f0-a13a-6b7d55ca813e · inbound

RULER: What's the Real Context Size of Your Long-Context Language Models? cites this paper.

RULER: What's the Real Context Size of Your Long-Context Language Models? LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T03:55:20.499754Z

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=2026-05-11T03:55:20.355345Z digest=sha256:61a06db56e8b70810bc4d7e10573ff021474e53d1b8d8637356c9bd0116e81a5

Observation e8114e81-b328-4198-992a-a918c9f378f4 · inbound

CoDec: Prefix-Shared Decoding Kernel for LLMs cites this paper.

CoDec: Prefix-Shared Decoding Kernel for LLMs LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 23

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unresolved
no resolver link, observed 2026-08-07T14:47:55.953578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:47:55.953578Z digest=sha256:81e6308297d489739d1ee4395a2e4a01f2220b38cd4f882bdbb5e26ae48e0875

Observation 3d86bd1c-67f3-433f-be8f-efe12fbd9652 · inbound

The Eye of Sherlock Holmes: Uncovering User Private Attribute Profiling via Vision-Language Model Agentic Framework cites this paper.

The Eye of Sherlock Holmes: Uncovering User Private Attribute Profiling via Vision-Language Model Agentic Framework LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 19

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unresolved
no resolver link, observed 2026-08-07T14:23:08.472628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:23:08.472628Z digest=sha256:1d1de2f4769b376e2a8d263145be47b1e6b741471163916a25326e7648cfe2f1

Observation 00993ed0-2ba8-433d-b8ba-24bacf7d5cc5 · inbound

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? cites this paper.

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:20:25.205683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:20:25.205683Z digest=sha256:0889237ad3641fc6a7ab1515d84c1daea005996bdaf1248f737a0aeb0286aeda

Observation 4f1356eb-550a-43fe-a223-83c4670af8f6 · inbound

Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model cites this paper.

Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:18:28.415429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:18:28.415429Z digest=sha256:6f59461168198d6a4ed44e359fdb4171210b4b1e78cdb2509b645e5ed16f9873

Observation c563a4cc-dee0-4af1-a8ad-1ab6b3cadab3 · inbound

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models cites this paper.

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 49

Resolution
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no resolver link, observed 2026-08-07T14:08:10.341641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.341641Z digest=sha256:0bf5dbbd459293087b21e3b70f24f67d18261941d205664ae430fbcfc12d6ef5

Observation 459a1f4f-2e60-4e3a-bc27-7589c020bc5d · inbound

Structured Memory Mechanisms for Stable Context Representation in Large Language Models cites this paper.

Structured Memory Mechanisms for Stable Context Representation in Large Language Models LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T12:59:44.397886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:59:44.397886Z digest=sha256:8fbd4553663444dc01805cfedf130fe7d31c10933bae175c228fb78e3db0c509

Observation d8fba2f6-3aa6-4199-9bcf-84072ca3e2e8 · inbound

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models cites this paper.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:41.800526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.800526Z digest=sha256:820c4210b875dafcf3596e608870d2bcf3566cd3dc984a47247104c1c0e8d07d

Observation 15cd5cb7-6c85-4d8e-998e-4bf9a0f4ecde · inbound

NovelHopQA: Diagnosing Multi-Hop Reasoning Failures in Long Narrative Contexts cites this paper.

NovelHopQA: Diagnosing Multi-Hop Reasoning Failures in Long Narrative Contexts LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 17

Resolution
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no resolver link, observed 2026-08-07T15:31:43.324780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:31:43.324780Z digest=sha256:a41740c88f29d530a5419583067b67f6909634dd6dbc3fafeeb7df0091380c10

Observation 4d23e3b7-e1cd-4d13-98d1-9b1cec73fe40 · inbound

Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis cites this paper.

Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T04:35:13.807586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:35:13.807586Z digest=sha256:9fafc2b05501f7d4a48b23441e293b83d76efab8f911df710ae6052aaab53094

Observation 7296fab3-dbf6-4710-8518-a527f67a5e80 · inbound

CROP: Circuit Retrieval and Optimization with Parameter Guidance using LLMs cites this paper.

CROP: Circuit Retrieval and Optimization with Parameter Guidance using LLMs LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T20:42:01.222247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:42:01.222247Z digest=sha256:68e54bf9d4a66069995e42bbb1a0aece10fc3ade0fa5e6cf4dc515eed943d2b9

Observation fde5c43f-c7c7-4108-beb7-ee6ba6c6846a · inbound

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions cites this paper.

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T21:20:22.227689Z

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=2026-05-16T21:20:22.146417Z digest=sha256:06e94e7ea2650100150389613d95a0e4adc326246e6f176f5940b22f8c5003fc

Observation e45dec87-cd28-41f6-a99b-9bc62595d241 · inbound

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions cites this paper.

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T19:36:05.716774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:36:05.716774Z digest=sha256:1653c836db8109a5fd536f24fa6a9aea491f257135d5de6c94f5f1da379b3810

Observation 4cd54c29-22ae-4b4a-9ee4-ef4433a885bb · inbound

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems cites this paper.

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T14:56:12.132513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:56:12.132513Z digest=sha256:7d3a23118fd75d47d228fa70fa04b2454493e82f04b2417989a7785479e54b87

Observation f8f93946-ae3b-4794-b1b9-5d96e3f486ea · inbound

A Distributed Learned Hash Table cites this paper.

A Distributed Learned Hash Table LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T18:46:56.553622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:46:56.553622Z digest=sha256:2dcff301e3f0a59bfc240b3d5363f6d043c5e7fde29daf5c4bb0a57851db540c

Observation 1082e52f-fa3f-4e6b-8cac-9f4715bc2e14 · inbound

Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework cites this paper.

Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T05:45:02.906907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:45:02.906907Z digest=sha256:7e512766b470ff7adc26dffe320b3556568f22535999a3ab0d331e92b9785958

Observation 1ceb92be-8166-4e1a-b050-a3cb7b97db2d · inbound

vAttention: Verified Sparse Attention cites this paper.

vAttention: Verified Sparse Attention LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T11:21:07.611750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:21:07.611750Z digest=sha256:78c79e09936b225dc6362da778974eead30ab67e3a301bf54f6c99ff18ffe5ce

Observation 1fb7c636-3ad2-4722-9b72-0e226f083feb · inbound

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs cites this paper.

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:51:08.901259Z

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=2026-05-18T08:48:47.128799Z digest=sha256:f6f3714bba22269f88a4cb701e5b2d52b6fcd5af7c8e3e5ee459d56cb50aa0da

Observation a44afe7e-bf12-4c0e-ac86-c5d5494b008f · inbound

ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache cites this paper.

ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:10:54.970457Z

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=2026-05-10T18:16:49.292491Z digest=sha256:e6552bfec38a08878b751387dabbe9cfdbb6e990521dc8c76bf78b4d90dfdfa3

Observation 9c9d0e34-f0d6-4381-a68b-8b7c264b8d16 · inbound

Tutti: Making SSD-Backed KV Cache Practical for Long-Context LLM Serving cites this paper.

Tutti: Making SSD-Backed KV Cache Practical for Long-Context LLM Serving LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:31:10.402070Z

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=2026-05-09T16:19:33.613685Z digest=sha256:6e5bab472cfc9269ac64b75e30b8615030b0da7fbd0f4dd837998c4cb86325f0

Observation 433505f0-c068-4d55-900a-75b9a785f9c3 · inbound

Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection cites this paper.

Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-20T09:18:10.126789Z

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=2026-05-20T09:16:56.388348Z digest=sha256:fc57b2dd4aa77682b3103364795cf1dba85f9bcc1a7d0989fdbe36fb1d0da63a

Observation 276510a3-3d82-4250-989e-fbd9d68befb3 · inbound

Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks cites this paper.

Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:00:21.893214Z

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=arxiv_source observed=2026-05-25T04:58:15.184063Z digest=sha256:eb317df4c4a5fa08ec61e7bb348e97372ea0abb230038708a900eef49d0f348d

Observation 5f19e6e1-f9e0-4b05-8c52-dfb21626930a · inbound

Training and Evaluating Diffusion Policies with Long Context Lengths cites this paper.

Training and Evaluating Diffusion Policies with Long Context Lengths LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-12T13:49:10.591494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:49:10.591494Z digest=sha256:5a6afce94c89e5356daac22560f97457693fe12c2006c637368c5187bf8f2de4

Observation 14b7e505-de31-4393-8549-32432e76bf50 · inbound

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling cites this paper.

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:03:51.883729Z

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=arxiv_source observed=2026-06-29T04:59:00.304723Z digest=sha256:33a2c93eeebc527d688a6b3143f258c12b80c75cdf4576989b2bae25b18010fa

Observation e1704b7e-b88f-48a8-a874-4be9b5913f01 · inbound

MicroAgent: Context-Augmented Multi-Agent Framework for Automatic Microservice Decomposition cites this paper.

MicroAgent: Context-Augmented Multi-Agent Framework for Automatic Microservice Decomposition LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-06-30T13:44:41.800464Z

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=2026-06-30T05:46:03.623076Z digest=sha256:a6938876667b292f57e3d4a6c3e397314e0629306db8efe777fbc94045594dc3