Paper Citation Record · LEDGER

Core Context Aware Transformers for Long Context Language Modeling

As of 17 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.12465.

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

pith.paper-citation-record.v1
2412.12465 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:11:39.748585Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

27 of 27 outbound references displayed

verified exact0
verified fuzzy10
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f7a503cc-f96d-407b-9d26-69efd1364aca · outbound

This paper cites Same as demonstrated in existing methods (Beltagy et al., 2020; Xiao et al., 2024b).

Core Context Aware Transformers for Long Context Language Modeling Same as demonstrated in existing methods (Beltagy et al., 2020; Xiao et al., 2024b)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.105767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b396aef2-ebad-4247-940c-1fdd7b936e8a · outbound

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

Core Context Aware Transformers for Long Context Language Modeling Extending Context Window of Large Language Models via Positional Interpolation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.602020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6846c3a-590f-4ab2-be44-6dd2f6cead4c · outbound

This paper cites Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers.

Core Context Aware Transformers for Long Context Language Modeling Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.611527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d528daf-9b2b-4e23-8339-e90b4599b224 · outbound

This paper cites LongNet: Scaling Transformers to 1,000,000,000 Tokens.

Core Context Aware Transformers for Long Context Language Modeling LongNet: Scaling Transformers to 1,000,000,000 Tokens

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.616699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f06184fe-5287-4e72-8eca-abde9a2d60e2 · outbound

This paper cites Data Engineering for Scaling Language Models to 128K Context.

Core Context Aware Transformers for Long Context Language Modeling Data Engineering for Scaling Language Models to 128K Context

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.622030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aa06aaf-5711-4cca-85b1-fdfbe526fe3f · outbound

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

Core Context Aware Transformers for Long Context Language Modeling DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.626849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64ff5deb-44bb-45a3-beb8-45b7e5b24b31 · outbound

This paper cites s 256 512 1024 2048 4096 PPL ↓ 2.98 2.92 2.86 2.79 2.73 Latency ↓ (ms) 457.4 460.1 461.4 462.8 473.1 Effect of Different Updating Strategies.

Core Context Aware Transformers for Long Context Language Modeling s 256 512 1024 2048 4096 PPL ↓ 2.98 2.92 2.86 2.79 2.73 Latency ↓ (ms) 457.4 460.1 461.4 462.8 473.1 Effect of Different Updating Strategies

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.070137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c2fed794-ad54-46dc-85a7-6ccf3308cfd2 · outbound

This paper cites an unresolved cited work.

Core Context Aware Transformers for Long Context Language Modeling Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:11:40.248786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1601e86a-3514-4c59-8df0-9c6a8056f98f · outbound

This paper cites GPT-4 Technical Report.

Core Context Aware Transformers for Long Context Language Modeling GPT-4 Technical Report

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.654390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff27d7e-ce5e-4b83-9e6b-e3a11d3f3680 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Core Context Aware Transformers for Long Context Language Modeling LLaMA: Open and Efficient Foundation Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.668374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3935e5ac-b689-4170-93a0-c63a56593019 · outbound

This paper cites Qwen2.5 Technical Report.

Core Context Aware Transformers for Long Context Language Modeling Qwen2.5 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.673740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a55eb01a-948a-456f-8c96-6ffa2b6848ba · outbound

This paper cites The MMLU benchmark spans 57 diverse subjects, ranging from elementary mathematics to professional law.

Core Context Aware Transformers for Long Context Language Modeling The MMLU benchmark spans 57 diverse subjects, ranging from elementary mathematics to professional law

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.232662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d37893a3-37fc-46b9-acb0-76cc17b11a98 · outbound

This paper cites base frequency.

Core Context Aware Transformers for Long Context Language Modeling base frequency

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.216143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 064f819b-70ea-4a43-9ac2-460d48dc0ec2 · outbound

This paper cites This enables us to integrate our CCA-Attention as a standalone, cache-friendly operator, effectively eliminating redundant computations.

Core Context Aware Transformers for Long Context Language Modeling This enables us to integrate our CCA-Attention as a standalone, cache-friendly operator, effectively eliminating redundant computations

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.198829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3518ab91-f9e6-4a8b-9662-049c403156cb · outbound

This paper cites Our experiments are based on the LLaMA-2 7B model fine-tuned on sequences of length 32K and 80K (Fu et al., 2024).

Core Context Aware Transformers for Long Context Language Modeling Our experiments are based on the LLaMA-2 7B model fine-tuned on sequences of length 32K and 80K (Fu et al., 2024)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.173335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da97c928-c70e-4f82-b2f3-acba2bf192c7 · outbound

This paper cites 16 Core Context Aware Transformers for Long Context Language Modeling C.

Core Context Aware Transformers for Long Context Language Modeling 16 Core Context Aware Transformers for Long Context Language Modeling C

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.138276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f413f8ae-88d1-4e42-88b5-ddf611e7213e · outbound

This paper cites an unresolved cited work.

Core Context Aware Transformers for Long Context Language Modeling Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:11:40.122478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7b4178f-21bc-4802-9862-1a136bc3393e · outbound

This paper cites Strategy Mean Pooling Max Pooling CCA-Attention (Ours) PPL ↓ 2.99 2.99 2.85 Effect of Group Size g.

Core Context Aware Transformers for Long Context Language Modeling Strategy Mean Pooling Max Pooling CCA-Attention (Ours) PPL ↓ 2.99 2.99 2.85 Effect of Group Size g

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.087172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ed662da6-82bc-4bd2-8177-f90118a375c6 · outbound

This paper cites The perplexity rapidly converges within approximately the first 100 iterations and remains stable over 1,000 iterations.

Core Context Aware Transformers for Long Context Language Modeling The perplexity rapidly converges within approximately the first 100 iterations and remains stable over 1,000 iterations

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.051901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0e2e3f84-3068-4f03-9a30-9a7649d6668a · outbound

This paper cites an unresolved cited work.

Core Context Aware Transformers for Long Context Language Modeling Unresolved cited work

Reference 2000

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:11:40.152196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23c79c42-8f28-4294-b24e-edb9a870f05a · outbound

This paper cites DeepSeek-V3 Technical Report.

Core Context Aware Transformers for Long Context Language Modeling DeepSeek-V3 Technical Report

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.644086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c43a855a-abd8-40e3-a063-3ab388aad145 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

Core Context Aware Transformers for Long Context Language Modeling Retentive Network: A Successor to Transformer for Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.663274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 970488b0-c9e3-4845-b982-5811d154f108 · outbound

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

Core Context Aware Transformers for Long Context Language Modeling RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.638818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c96ee85-bc28-43e9-b57d-72b3dbe75c84 · outbound

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

Core Context Aware Transformers for Long Context Language Modeling LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.585247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e5a5456-13cc-4b3b-a090-19c543b30e14 · outbound

This paper cites Longformer: The Long-Document Transformer.

Core Context Aware Transformers for Long Context Language Modeling Longformer: The Long-Document Transformer

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.590791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 780698b2-f707-4bcb-a74d-c9aeed4745fe · outbound

This paper cites Chang, Y ., Wang, X., Wang, J., Wu, Y ., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y ., Ye, W., Zhang, Y ., Chang, Y ., Yu, P.

Core Context Aware Transformers for Long Context Language Modeling Chang, Y ., Wang, X., Wang, J., Wu, Y ., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y ., Ye, W., Zhang, Y ., Chang, Y ., Yu, P

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:11:40.270750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81609661-bbeb-4667-b9fa-27153bd0abb3 · outbound

This paper cites LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models.

Core Context Aware Transformers for Long Context Language Modeling LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.633204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.