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Paper Citation Record · LEDGER

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models

As of 11 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2501.13629.

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

pith.paper-citation-record.v1
2501.13629 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:50:22.077513Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:32:31.119922Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T03:37:00.945663Z

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved46
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c94ecbd-862a-4fe4-ab6c-55395bb102d1 · outbound

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

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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source=pdf_text observed=2026-08-10T15:50:21.815849Z digest=sha256:ded4b4ec4ee17a0401d68d2f1a874ae9707f894670958161582c0a94ba4dc984

Observation f15bdfe8-a257-4a2b-99f6-332d94dff2e6 · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.064477Z digest=sha256:840368d2582b9679646000634251f5f5bd7b605416a426f9e07b41cd33be1f8b

Observation 975c55ac-f182-4b34-9ee7-74e2f95ebfab · outbound

This paper cites Stable LM 2 1.6B Technical Report.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Stable LM 2 1.6B Technical Report

Reference 5

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source=pdf_text observed=2026-08-10T15:50:21.836712Z digest=sha256:0350b6a5af4e782b30fda63bb27ba774b93d219639bb4a1f2ce8e7d844ed36a2

Observation 278f5b85-2afd-4c40-b38b-280b2bcc6710 · outbound

This paper cites Longformer: The Long-Document Transformer.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Longformer: The Long-Document Transformer

Reference 6

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source=pdf_text observed=2026-08-10T15:50:21.841537Z digest=sha256:b5c52546e156ec7e8eb4255db6259b3d4ca86cd542ec5104ebdbfded47ab4bfc

Observation def6a48e-8f04-4e46-a548-266286d98b33 · outbound

This paper cites Large Language Monkeys: Scaling Inference Compute with Repeated Sampling.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 8

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source=pdf_text observed=2026-08-10T15:50:21.851361Z digest=sha256:d626649f365c9082484a5719d120753901e5e3420546ce2308e94c56279a01e5

Observation 5fc5cdeb-a7c1-4b39-9625-dbc7b46180be · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 9

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source=pdf_text observed=2026-08-10T15:50:21.856599Z digest=sha256:c86321cb24260ae369a06dcdf528c01d7ae636365b3e9e3f35800dbce423819d

Observation 035c2ef5-0855-4056-8ba5-6fac47e83ee7 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Evaluating Large Language Models Trained on Code

Reference 10

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source=pdf_text observed=2026-08-10T15:50:21.861854Z digest=sha256:566a7125c5d6ce36639ea22a1261d1aa542b75bc9fe84a353af24cfeed572298

Observation 295a5ccb-bbeb-4423-8888-ce02474df9ff · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 11

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source=pdf_text observed=2026-08-10T15:50:21.866755Z digest=sha256:5c83e6f7d5c0999321e3a839a54877afafe31824813ff406f222806a4e8278f7

Observation 062b003f-1df7-44e2-8f13-5c5db5248b25 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 14

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source=pdf_text observed=2026-08-10T15:50:21.880969Z digest=sha256:ff15ac8aecfe9f8c768c8939d51856dad330a785d1e8a252db1f9776332a154c

Observation 439cc4b4-6d82-4bad-9ff3-74072317e416 · outbound

This paper cites Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster

Reference 15

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source=pdf_text observed=2026-08-10T15:50:21.885970Z digest=sha256:c7b90a4654a4681d321ab598c19b2620dcf1448f992f640c96778314fc3b1e76

Observation 829f0445-1862-4a57-9094-7be4c354c2ad · outbound

This paper cites The Llama 3 Herd of Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models The Llama 3 Herd of Models

Reference 16

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source=pdf_text observed=2026-08-10T15:50:21.891051Z digest=sha256:db449d4695aef23a44ea67daa37cc32bc5aa7e3ee1ba0d330131b656e4fc27a2

Observation 24c2ab63-4ef5-482e-a2b8-e449b945103d · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 17

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source=pdf_text observed=2026-08-10T15:50:21.895633Z digest=sha256:d91642c5daba2780780c8f1ee6851c9f6c194c360a11f86a3e0d7c2c66c3b1fc

Observation 3ee3c350-8471-4513-b338-7772702138d9 · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models OLMo: Accelerating the Science of Language Models

Reference 18

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source=pdf_text observed=2026-08-10T15:50:21.900910Z digest=sha256:7c3c7fbcc05ab657f6e16f789a06bbf82a1a25d3960fef62b79c8c632591f03f

Observation 1d893888-6a44-44b9-84fd-15ad4464c20f · outbound

This paper cites Textbooks Are All You Need.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Textbooks Are All You Need

Reference 19

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source=pdf_text observed=2026-08-10T15:50:21.905868Z digest=sha256:809f8126d9b85b38f34ac0be24fb367657d5608e0847ce98346164ef8cb8f9d5

Observation 61e915ce-4f28-43bb-8fb5-cc32721a0b38 · outbound

This paper cites Memory-efficient Transformers via Top-$k$ Attention.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Memory-efficient Transformers via Top-$k$ Attention

Reference 20

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source=pdf_text observed=2026-08-10T15:50:21.911004Z digest=sha256:670b91c20cbe617dd7eefdf523ac3e81889065f3ee5bfc092b94c4de7ee8734e

Observation 5691c93a-99ce-47cf-8d30-535656870aea · outbound

This paper cites LM-infinite: Zero-shot extreme length generalization for large language models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models LM-infinite: Zero-shot extreme length generalization for large language models

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:21.915897Z digest=sha256:3edd43b4157077ef68cb1b8d11d10a8c38a889bc1c942f37ba1bbf8596125f1d

Observation 274c669d-aec4-49be-8811-1b201ef457fe · outbound

This paper cites FastDecode: High-Throughput GPU-Efficient LLM Serving using Heterogeneous Pipelines.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models FastDecode: High-Throughput GPU-Efficient LLM Serving using Heterogeneous Pipelines

Reference 22

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source=pdf_text observed=2026-08-10T15:50:21.920956Z digest=sha256:29cc376f3cf3be3c62b5c56afa67b7872e0f6335dba4be7c235e815215f5780c

Observation 635abfae-34d2-4df7-bd5b-1490ff86acbe · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Measuring Massive Multitask Language Understanding

Reference 23

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source=pdf_text observed=2026-08-10T15:50:21.925987Z digest=sha256:bfa700bfc2b1827017b9cbbccee57695384d43bf8b4ef986c350455328a6d338

Observation b8535ed5-d8a8-4581-8a44-f55c0c1ba4f5 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 24

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source=pdf_text observed=2026-08-10T15:50:21.931406Z digest=sha256:678343914572f4e9665ea72a5cd39491b102c3878a5c45c4d416aa6c569c120b

Observation 46a89846-debf-453c-b16b-631f7528a2b8 · outbound

This paper cites Scaling Laws for Neural Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Scaling Laws for Neural Language Models

Reference 25

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source=pdf_text observed=2026-08-10T15:50:21.936172Z digest=sha256:3ea1bc7e7195054052b0a2f02f9172845597cfae930370542d238d5e51b606e6

Observation 9594843b-cf1a-45de-9518-f2d03e9cac62 · outbound

This paper cites DataComp-LM: In search of the next generation of training sets for language models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models DataComp-LM: In search of the next generation of training sets for language models

Reference 26

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source=pdf_text observed=2026-08-10T15:50:21.942092Z digest=sha256:74cf22efb71f1724b774fb1e78f9d28143cfcf4c4402b61a0389227e96c4b0df

Observation 50ebd4a3-c042-4000-9574-e7d66d5ddbf4 · outbound

This paper cites LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 27

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source=pdf_text observed=2026-08-10T15:50:21.946677Z digest=sha256:f60d96175d032ebacddc00e9c3fb3724de4ef6ecaacb6d360c2e43f6aa7c3d35

Observation cbffae5e-3259-40a6-8775-7bd309d8af21 · outbound

This paper cites MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Reference 28

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source=pdf_text observed=2026-08-10T15:50:21.951455Z digest=sha256:c28208b4b6676dca6813f4abe4b2b9122e09d17d247b792d8128c50c691ac588

Observation bd1c4c82-473f-4bf9-82d3-8dcd390411cf · outbound

This paper cites OpenELM: An Efficient Language Model Family with Open Training and Inference Framework.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

Reference 29

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source=pdf_text observed=2026-08-10T15:50:21.955933Z digest=sha256:6d53e3a1dd1b84fc8cec13b5cc5eb01d2800220a8bb94265ff77c14fcb1f99e4

Observation 935baa46-b278-4059-94c9-4216709a48d9 · outbound

This paper cites Crosslingual Generalization through Multitask Finetuning.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Crosslingual Generalization through Multitask Finetuning

Reference 30

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source=pdf_text observed=2026-08-10T15:50:21.960583Z digest=sha256:e6a26292989a1b4918824771f29ef476b8d84dee18151807818442962908e437

Observation 09ae0fca-2fec-4119-865b-cfcc12c788e2 · outbound

This paper cites Fast Transformer Decoding: One Write-Head is All You Need.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Fast Transformer Decoding: One Write-Head is All You Need

Reference 32

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source=pdf_text observed=2026-08-10T15:50:21.973704Z digest=sha256:a62034cad0ac9dec430f5ab4ff58ddd4702f50981d282aaf124419194907b7f2

Observation 87415344-5f4d-4e26-837e-257f1bcaa594 · outbound

This paper cites You Only Cache Once: Decoder-Decoder Architectures for Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models You Only Cache Once: Decoder-Decoder Architectures for Language Models

Reference 33

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source=pdf_text observed=2026-08-10T15:50:21.978594Z digest=sha256:d395b53da5718d2351b5240bd521d77d385d4854ce0ee55b2779cf1745f988dd

Observation 8fb2f21f-e0ef-42ee-8ea8-e223838bbc8b · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 34

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source=pdf_text observed=2026-08-10T15:50:21.983664Z digest=sha256:b2c9d0140ecb03c18c33586bd931582b8da0e41a7bf53579b8f3fa6f7d58b92c

Observation 7adfde4e-8019-41b0-b75e-bfa92e2aef56 · outbound

This paper cites Crowdsourcing Multiple Choice Science Questions.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Crowdsourcing Multiple Choice Science Questions

Reference 37

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source=pdf_text observed=2026-08-10T15:50:21.998284Z digest=sha256:f62309f1ff48b13be1e167c9bf02b18cac1ac9adcd3952b1dc1a99f0ff1bac4e

Observation eb0ca9fb-c7d5-43a6-98d7-ad840d762eda · outbound

This paper cites DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Reference 38

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source=pdf_text observed=2026-08-10T15:50:22.003332Z digest=sha256:60a71c3272065b5ae226be2ee395d48247f281bad979116fdb0b860bee29058e

Observation b910b473-1d98-4a38-bb75-b07b9fc2a918 · outbound

This paper cites Qwen2 Technical Report.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Qwen2 Technical Report

Reference 39

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source=pdf_text observed=2026-08-10T15:50:22.008336Z digest=sha256:9646fb53125903cc39245c55bfc047df2569006221d83a36c1c61ba75a30890c

Observation ea036654-4797-48a1-85ee-43b240bba0bd · outbound

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

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 40

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source=pdf_text observed=2026-08-10T15:50:22.012847Z digest=sha256:e47d96e7b8b804657bbb5727605bec828e7ee098a300ff8eeac8cb7c3ba2e338

Observation bb604531-9f86-4a95-a722-a19aae6b7d90 · outbound

This paper cites TinyLlama: An Open-Source Small Language Model.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models TinyLlama: An Open-Source Small Language Model

Reference 41

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source=pdf_text observed=2026-08-10T15:50:22.017958Z digest=sha256:eb4cb88d4cea67cb0156bcb701a11d9bdde4540fa7ef8e20337575af5c8d3f79

Observation 8e693bb6-c968-4365-b2b1-5fe037c91411 · outbound

This paper cites A Survey on Efficient Inference for Large Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models A Survey on Efficient Inference for Large Language Models

Reference 42

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source=pdf_text observed=2026-08-10T15:50:22.023813Z digest=sha256:cdb46058578746d3f8d9c92292e8d670c0cfa74f496979151f3bdb6ebfd445c7

Observation 4ad9a14d-aa44-4051-baf3-e91343b9ea33 · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-10T15:50:22.029281Z digest=sha256:04a9041711c7386b878c8d7d32495d147ffb538003b3bbb1538f3e539c11cfaf

Observation 57436a0e-d8d3-464e-9265-fec22c8ab6b7 · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 44

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source=pdf_text observed=2026-08-10T15:50:22.034114Z digest=sha256:f898a59a1fbc86185013e26325625b1e9ac0b934f3f8ab01045d11bfc1a8d399

Observation 11b3c6bb-3722-444c-825b-b1afd5d9021d · outbound

This paper cites MQA is a variant of the standard Multi-Head Attention (MHA) mechanism, where all query heads share a single key head and value head.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models MQA is a variant of the standard Multi-Head Attention (MHA) mechanism, where all query heads share a single key head and value head

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:22.947879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.039598Z digest=sha256:1b3d8110f078f9e2f3ca1abc9af139d98d48feb92cf6723c3aa40c274d3bd456

Observation 5f356d01-08c5-4785-8ea8-fdd48ee032cb · outbound

This paper cites This operation significantly enhances inference efficiency by reducing memory usage.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models This operation significantly enhances inference efficiency by reducing memory usage

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:22.917344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.049757Z digest=sha256:835eced4b71c79ef4abdfdb94684c265af2c92a2ccca458c1da62e3390dc8b6c

Observation c40c6226-cc4a-4d8c-b9e4-8d0d8c9105b2 · outbound

This paper cites Sel.V-top100.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Sel.V-top100

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:22.900479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.055569Z digest=sha256:8a86158d596e4e01664cfcfa3f5e6aa6e3ae5333ce5bb8b83bdb81982ccc1f61

Observation 76baeb35-e653-4ecf-b9e0-af6f355cfb82 · outbound

This paper cites We utilize the same vocabulary as Llama3 (Dubey et al., 2024), with a vocabulary size of 128k.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models We utilize the same vocabulary as Llama3 (Dubey et al., 2024), with a vocabulary size of 128k

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:22.883032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.059879Z digest=sha256:e6ccc99e8aefb258c89fcfef3296bd0be055d54462ae1ef88090e82d8a3b4b21

Observation df503ac4-0015-466c-965c-7ff532b32281 · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:50:22.849794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.068540Z digest=sha256:8d84fc179e01bc96ec81a5002467661f95e23ebe556c7175225d7c8a494d1c44

Observation 06476e3c-9832-40d5-81aa-3028b31efde2 · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:50:22.832044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.073236Z digest=sha256:538d2d70bafd2ebde2ca590341efe94617bcf4f9c681cc4226e140118ea2f96e

Observation 4cbb45b9-6355-44b6-819d-8a3c5b23bdbe · outbound

This paper cites The evaluation results on various general, coding and math problem-solving benchmarks are shown in Table.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models The evaluation results on various general, coding and math problem-solving benchmarks are shown in Table

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:22.815410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.077513Z digest=sha256:7bad8b9ac598a59486e0bb9c649900f92712652d9b31260d8dd1abd53dd3df5a

Observation f6103bd0-c76c-49ba-a690-9e296062065f · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.964947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.964947Z digest=sha256:045924380eecf36757e177bed1be29a410e175cd561dc13068f6fea455c52f79

Observation 7cc7a532-dd2d-43f2-973c-29bb34010358 · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.993095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.993095Z digest=sha256:8940edad5be6c4cde21946a2da292fb9dfb39bff27df34276e833fd24e1b3bb0

Observation fc2e5ab9-fa6a-48df-824a-4ae84726c406 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Training Verifiers to Solve Math Word Problems

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.876185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.876185Z digest=sha256:651745e5f8a6138b42079e340b81d42c7f8d702b49d2b750282c5da7394199ea

Observation 4bb69983-4524-4a16-aaa7-9f5efa17537a · outbound

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

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.871591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.871591Z digest=sha256:92dd6795fb345d4351c81b001b7bc3fe7ae4e0a4a3613dcafd12c59d2ac23544

Observation 2a8512ca-d088-4f2a-b192-7d6577b5871b · outbound

This paper cites Reducing Transformer Key-Value Cache Size with Cross-Layer Attention.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.846487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.846487Z digest=sha256:444ea27d55d21a5fbefd26bceb75ae0264e21d5e2d4ba3993f077c239d0cfc35

Observation be63b3b5-8dd8-49ae-979b-8de0f1878524 · outbound

This paper cites Llemma: An Open Language Model For Mathematics.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Llemma: An Open Language Model For Mathematics

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.831787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.831787Z digest=sha256:996ac9db14ebade8837796f425c28af0eeab33bb418802b9205a922979bce5b6

Observation 9f848709-c9fe-4e2b-a873-8d53b114eaff · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.988323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.988323Z digest=sha256:5b1917f15a7ed9e2728f47a278755d727f4f1c302724c500d52d81caad71f798

Observation 6253936d-fde1-4d71-91ac-ec2a0ebd7546 · outbound

This paper cites GQA: Training general- ized multi-query transformer models from multi-head checkpoints.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models GQA: Training general- ized multi-query transformer models from multi-head checkpoints

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:50:23.014540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:21.822080Z digest=sha256:389a7c50677f136213a34a708221671547f9ef8f29bad607a00c7e9dff2ebc27

Observation 4912977d-a85e-4533-baaf-f934a7d80f5a · outbound

This paper cites Program Synthesis with Large Language Models.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Program Synthesis with Large Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T15:50:21.826854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:50:21.826854Z digest=sha256:e39261c245ee5f65de31a044dcf9e908bf031f73cb167319bcd2847aac130beb

Observation a4a29beb-0ceb-4799-893c-080363cfe96f · outbound

This paper cites an unresolved cited work.

Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Unresolved cited work

Reference 2048

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:50:22.932979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T15:50:22.044486Z digest=sha256:17a2139fb6673308d4f6b98b7b9d63ed75a0af4bb38b85c3a1e764c72b1d401a

Pith citing papers

Observation 8e4c7db0-b686-4cbb-8373-b9af37adc193 · inbound

Hardware-Efficient Attention for Fast Decoding cites this paper.

Hardware-Efficient Attention for Fast Decoding Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:31.119922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:32:31.119922Z digest=sha256:99379f41a89241f2af68167b29af8d824462a34b0a5d79eb2beeac82ab5ea0f8

Observation 52228e1e-b7f4-4c6d-8b9c-bc7f199c4f61 · inbound

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training cites this paper.

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:37:00.948390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-19T03:36:50.366757Z digest=sha256:9b91edcab6343c69bfa64ebb7517a4d137e1c378e774b975401e8c350de7cbcc