Paper Citation Record · LEDGER

Efficient Pretraining Length Scaling

As of 18 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 4 inbound Pith citation observations for arXiv:2504.14992.

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

pith.paper-citation-record.v1
2504.14992 v2

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:40:27.825037Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:31:30.334937Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T07:43:11.766620Z

Reference resolution

63 of 63 outbound references displayed

verified exact0
verified fuzzy12
unresolved50
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a495a46-b68e-4c72-b08b-8ed75d565a47 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Efficient Pretraining Length Scaling Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.558018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37f726f6-5bd4-452b-b1ee-51c5db3e5e8e · outbound

This paper cites Gqa: Training generalized multi-query transformer models from multi-head checkpoints.

Efficient Pretraining Length Scaling Gqa: Training generalized multi-query transformer models from multi-head checkpoints

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.563405Z

Source-reported events for the cited work

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Observation 15b54ffb-3f76-4735-b1f1-a3cc8cfe9928 · outbound

This paper cites Longformer: The Long-Document Transformer.

Efficient Pretraining Length Scaling Longformer: The Long-Document Transformer

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.567873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36e29e45-f8e2-4088-83a9-6c5861deb028 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language.

Efficient Pretraining Length Scaling Piqa: Reasoning about physical commonsense in natural language

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.572503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 091c1abf-aee0-4067-8db9-777408e2aedd · outbound

This paper cites Striped Attention: Faster Ring Attention for Causal Transformers.

Efficient Pretraining Length Scaling Striped Attention: Faster Ring Attention for Causal Transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.576790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0f1e1f3-92a8-43a5-b4ed-aa5dc82d590b · outbound

This paper cites Step-level Value Preference Optimization for Mathematical Reasoning.

Efficient Pretraining Length Scaling Step-level Value Preference Optimization for Mathematical Reasoning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.581679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9ecf90b-d3f6-4c55-ae68-2d61dd38abc3 · outbound

This paper cites Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking.

Efficient Pretraining Length Scaling Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.586615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d98a2357-b202-48e5-ad30-4a0bf0bd91ea · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Efficient Pretraining Length Scaling Generating Long Sequences with Sparse Transformers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.591194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9e293a4-de22-4678-9395-6af6dcc67457 · outbound

This paper cites Unified scaling laws for routed language models.

Efficient Pretraining Length Scaling Unified scaling laws for routed language models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.595724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80048c91-2a95-4320-867c-e50c8cc87163 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Efficient Pretraining Length Scaling Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.599886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 665c3ae4-19f4-4b9f-bc13-659ac7dbb42b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Efficient Pretraining Length Scaling Training Verifiers to Solve Math Word Problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.604174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8c855b-09c9-45d8-a140-9ace5b336d3f · outbound

This paper cites Flashattention-2: Faster attention with better parallelism and work partitioning.

Efficient Pretraining Length Scaling Flashattention-2: Faster attention with better parallelism and work partitioning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.816535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c858dc2e-bee8-45ca-b2d5-c2fbc0795e09 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher Ré.

Efficient Pretraining Length Scaling Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.803359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a35e5cf4-34aa-4230-be4f-26896c2c47d0 · outbound

This paper cites Flash-decoding for long-context inference, October.

Efficient Pretraining Length Scaling Flash-decoding for long-context inference, October

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.789928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0fcddfd9-b261-4dee-aa43-098683fe5ded · outbound

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

Efficient Pretraining Length Scaling LongNet: Scaling Transformers to 1,000,000,000 Tokens

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.624969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90fe73a9-05d6-4945-bf02-11a2bcb339ef · outbound

This paper cites Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach.

Efficient Pretraining Length Scaling Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.629386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c26e4082-807b-40ae-a037-b99d19b14464 · outbound

This paper cites Think before you speak: Training language models with pause tokens.

Efficient Pretraining Length Scaling Think before you speak: Training language models with pause tokens

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.763606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 92849502-2711-40bf-ae22-62a82284aab2 · outbound

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

Efficient Pretraining Length Scaling DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.638548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f7478eb-756e-4cf2-aecd-d02af900b175 · outbound

This paper cites PSYDIAL: Personality-based Synthetic Dialogue Generation using Large Language Models.

Efficient Pretraining Length Scaling PSYDIAL: Personality-based Synthetic Dialogue Generation using Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.642741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80155363-9798-4441-97c7-6b2949a45db3 · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space.

Efficient Pretraining Length Scaling Training Large Language Models to Reason in a Continuous Latent Space

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.646890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7afb1830-a59a-4eaf-b75e-33d7f4ffe78f · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Efficient Pretraining Length Scaling Measuring Massive Multitask Language Understanding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.651372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 209e70b9-66b9-4053-bb77-0f80cd91d6c9 · outbound

This paper cites Scaling Laws for Transfer.

Efficient Pretraining Length Scaling Scaling Laws for Transfer

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.655454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1b9f26b-e458-4b6f-9015-6ba6d282e343 · outbound

This paper cites FlashDecoding++: Faster Large Language Model Inference on GPUs.

Efficient Pretraining Length Scaling FlashDecoding++: Faster Large Language Model Inference on GPUs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.659632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 163c4d11-ee79-453a-af08-6709b56dad43 · outbound

This paper cites Mistral 7B.

Efficient Pretraining Length Scaling Mistral 7B

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.664264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca625383-aefd-4784-9ef3-633c5428580e · outbound

This paper cites Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention.Advances in Neural Information Processing Systems, 37:52481–52515, 2024.

Efficient Pretraining Length Scaling Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention.Advances in Neural Information Processing Systems, 37:52481–52515, 2024

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.669416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a06f4371-7320-412d-91cd-c08c3daec77f · outbound

This paper cites Longllmlingua: Accelerating and enhancing llms in long context scenarios via prompt compression.

Efficient Pretraining Length Scaling Longllmlingua: Accelerating and enhancing llms in long context scenarios via prompt compression

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.673545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 497d90ed-2ef1-463c-818a-3a55a1e04edd · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Efficient Pretraining Length Scaling SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.677625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e232f65-c2fc-48fb-afb6-a44fe20f03a4 · outbound

This paper cites Scaling Laws for Neural Language Models.

Efficient Pretraining Length Scaling Scaling Laws for Neural Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.681973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a5ddb20-51a2-40f5-a640-73dd082d3a0f · outbound

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

Efficient Pretraining Length Scaling Natural questions: a benchmark for question answering research

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.686173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3437b068-4646-4092-950c-17ae22082461 · outbound

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

Efficient Pretraining Length Scaling Efficient memory management for large language model serving with pagedattention

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.690438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9cee53b-3d09-4738-9c19-20f8869de968 · outbound

This paper cites MiniMax-01: Scaling Foundation Models with Lightning Attention.

Efficient Pretraining Length Scaling MiniMax-01: Scaling Foundation Models with Lightning Attention

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.694729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d8bb76-a3fe-4582-a07b-bc8dbe2f1d63 · outbound

This paper cites SnapKV: LLM Knows What You are Looking for Before Generation.

Efficient Pretraining Length Scaling SnapKV: LLM Knows What You are Looking for Before Generation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.698916Z

Source-reported events for the cited work

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Observation 689cae58-4f74-4dae-b1f9-6d8c08e0d3ea · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Efficient Pretraining Length Scaling DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.708789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e171f76d-316f-4c7e-ac7e-db93ce48ec98 · outbound

This paper cites DeepSeek-V3 Technical Report.

Efficient Pretraining Length Scaling DeepSeek-V3 Technical Report

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.713440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b540b48a-e3b9-4079-bcf0-63075bde9b1f · outbound

This paper cites Ring Attention with Blockwise Transformers for Near-Infinite Context.

Efficient Pretraining Length Scaling Ring Attention with Blockwise Transformers for Near-Infinite Context

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.717780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6970b460-588e-45a6-a150-d711cd57ba0a · outbound

This paper cites Cotformer: More tokens with attention make up for less depth.

Efficient Pretraining Length Scaling Cotformer: More tokens with attention make up for less depth

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.733667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 10601342-b229-4e83-bc93-b1f013364f00 · outbound

This paper cites 2 OLMo 2 Furious.

Efficient Pretraining Length Scaling 2 OLMo 2 Furious

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.726822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf7b5a91-4723-42d9-911b-62c308fbc876 · outbound

This paper cites Learning to reason with llms, 2024.

Efficient Pretraining Length Scaling Learning to reason with llms, 2024

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.730983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e15b3320-6f79-4d74-be8f-d37b62ddbe0a · outbound

This paper cites Learning to reason with llms, 2025.

Efficient Pretraining Length Scaling Learning to reason with llms, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.735013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e485649-1b75-42d9-b5bf-ab6eba06eb3f · outbound

This paper cites Vicky Zhao, Lili Qiu, and Dongmei Zhang.

Efficient Pretraining Length Scaling Vicky Zhao, Lili Qiu, and Dongmei Zhang

Reference 40

Resolution: malformed identifier; no resolver link, observed 2026-08-16T11:40:27.738918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a340972b-df2c-4a84-a40c-c1ea645abdda · outbound

This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

Efficient Pretraining Length Scaling Gpqa: A graduate-level google-proof q&a benchmark

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.742943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4498814-6522-4633-b142-e43347dd63db · outbound

This paper cites SparQ Attention: Bandwidth-Efficient LLM Inference.

Efficient Pretraining Length Scaling SparQ Attention: Bandwidth-Efficient LLM Inference

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.747393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91e7e568-39a5-4459-84a7-f28fa8143952 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021.

Efficient Pretraining Length Scaling Winogrande: An adversarial winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.751446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 942dcaf6-5bca-4dae-a22d-3cede4caf60c · outbound

This paper cites Proximal Policy Optimization Algorithms.

Efficient Pretraining Length Scaling Proximal Policy Optimization Algorithms

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.755193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ae0e7c7-7d5d-4826-8039-6c42aebce566 · outbound

This paper cites FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision.

Efficient Pretraining Length Scaling FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.759136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1ac3a2b-439b-4ba0-b529-fe90cf13ed15 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Efficient Pretraining Length Scaling DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.763275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdf1eecf-8b62-4f5e-81d5-ed42dee80707 · outbound

This paper cites Sparsebert: Rethinking the importance analysis in self-attention.

Efficient Pretraining Length Scaling Sparsebert: Rethinking the importance analysis in self-attention

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.676571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ffa160b7-62b5-4451-9cee-ba8cc6e5f20b · outbound

This paper cites LLM Pretraining with Continuous Concepts.

Efficient Pretraining Length Scaling LLM Pretraining with Continuous Concepts

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.771507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9651b31e-bf8a-4581-8fe1-d93d9bb3bc07 · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

Efficient Pretraining Length Scaling CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.775667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62ff530d-9287-492f-8f52-d4e11f830858 · outbound

This paper cites Quest: Query-aware sparsity for efficient long-context llm inference.

Efficient Pretraining Length Scaling Quest: Query-aware sparsity for efficient long-context llm inference

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.663361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9cf96c16-855e-49a5-a497-93f7bf9a3a39 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Efficient Pretraining Length Scaling Gemini: A Family of Highly Capable Multimodal Models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.784477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f878e569-4991-4ae0-9492-22124a6c8e85 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Efficient Pretraining Length Scaling Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.788641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7008f2f-ee9d-4ac4-906b-d724213ddca8 · outbound

This paper cites Spatten: Efficient sparse attention architecture with cascade token and head pruning.

Efficient Pretraining Length Scaling Spatten: Efficient sparse attention architecture with cascade token and head pruning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.792728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 087072a8-55d2-4a7f-9dfd-b557ca3f5767 · outbound

This paper cites Openhands: An open platform for ai software developers as generalist agents.

Efficient Pretraining Length Scaling Openhands: An open platform for ai software developers as generalist agents

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.796755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 506aa59f-7d7a-4a29-8cb5-61cd03e2d6d7 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advancesin neural information processing systems, 35:24824–24837, 2022.

Efficient Pretraining Length Scaling Chain-of-thought prompting elicits reasoning in large language models.Advancesin neural information processing systems, 35:24824–24837, 2022

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.800794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9b29f29-a0e1-4ad3-af00-201c0d2f4ad6 · outbound

This paper cites Efficient streaming language models with attention sinks.

Efficient Pretraining Length Scaling Efficient streaming language models with attention sinks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.633681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 742911d0-84db-4836-a71b-037ca41da3bb · outbound

This paper cites Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention.

Efficient Pretraining Length Scaling Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.808920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cb9823b-4fc8-4f12-bf00-ca70efdd8d24 · outbound

This paper cites Big bird: Transformers for longer sequences.

Efficient Pretraining Length Scaling Big bird: Transformers for longer sequences

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.620016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fccd7f9e-4885-43b9-83c7-359895c4e452 · outbound

This paper cites Quiet-star: Language models can teach themselves to think before speaking.

Efficient Pretraining Length Scaling Quiet-star: Language models can teach themselves to think before speaking

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.606051Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d34e39bc-7abd-4d54-8354-81e1d36388c6 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Efficient Pretraining Length Scaling HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.820980Z

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Observation 41be79ca-507e-42dd-9121-b032ca2660bb · outbound

This paper cites H2o: Heavy-hitter oracle for efficient generative inference of large language models.

Efficient Pretraining Length Scaling H2o: Heavy-hitter oracle for efficient generative inference of large language models

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.592405Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 100ce4b3-c7de-4b4b-953b-e3426844ab92 · outbound

This paper cites Accessed: 2024-9-29.

Efficient Pretraining Length Scaling Accessed: 2024-9-29

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:40:28.776898Z

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Observation 2cbdfd7b-e0f9-45b7-95e4-990a0b58189b · outbound

This paper cites SnapKV: LLM Knows What You are Looking for Before Generation.

Efficient Pretraining Length Scaling SnapKV: LLM Knows What You are Looking for Before Generation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T11:40:27.704329Z

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Pith citing papers

Observation 9e028773-dd76-486a-a7fa-06f751cc643f · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Efficient Pretraining Length Scaling

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:43:11.770485Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b3c40fe4-0676-45ed-83ed-00fe7703e31f · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Efficient Pretraining Length Scaling

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T07:31:30.334937Z

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Observation 7003648e-fb23-457e-9306-e412ae4fdc60 · inbound

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook cites this paper.

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook Efficient Pretraining Length Scaling

Reference 235

Resolution: unresolved; no resolver link, observed 2026-07-13T14:03:01.974171Z

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Observation f683faf2-3189-4eec-9029-366a612255d5 · inbound

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models cites this paper.

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models Efficient Pretraining Length Scaling

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:36:29.285778Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.