Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-21T06:39:04.312270Z
Paper Citation Record · LEDGER
Attention Residuals
As of 4 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 65 inbound Pith citation observations for arXiv:2603.15031.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T01:39:47.872763Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T14:57:14.484456Z
Reference resolution
75 of 75 outbound references displayed
- verified exact54
- verified fuzzy19
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2b40efc6-40ad-489e-9f48-e6740dc679d1 · outbound
This paper cites Program Synthesis with Large Language Models.
Attention Residuals Program Synthesis with Large Language Models
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.414073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6192be48-d836-4a44-82bd-1269e536e205 · outbound
This paper cites ReZero is All You Need: Fast Convergence at Large Depth.
Attention Residuals ReZero is All You Need: Fast Convergence at Large Depth
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.417303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 441d28d2-2bf6-495f-bc8c-0ce070ed4713 · outbound
This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.
Attention Residuals Neural Machine Translation by Jointly Learning to Align and Translate
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.358924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ededb4f2-dc48-44ff-bb08-78658201357b · outbound
This paper cites Post-layernorm is back: Stable, expressive, and deep.arXiv preprint arXiv:2601.19895, 2026.
Attention Residuals Post-layernorm is back: Stable, expressive, and deep.arXiv preprint arXiv:2601.19895, 2026
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.363263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 298f89b3-fe04-4f1f-be33-62f707f41c61 · outbound
This paper cites Evaluating Large Language Models Trained on Code.
Attention Residuals Evaluating Large Language Models Trained on Code
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.367229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4c65da4f-74cf-4e26-bdad-90bce18a2991 · outbound
This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.
Attention Residuals Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.371259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 22cb02d3-6414-4b9f-85e3-f362739900ae · outbound
This paper cites Training Verifiers to Solve Math Word Problems.
Attention Residuals Training Verifiers to Solve Math Word Problems
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.375096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eaa4aefc-9949-4d81-8514-366f7991cb07 · outbound
This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.
Attention Residuals Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.348285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1052907f-dc0a-478a-9758-ce4eb7dc85ad · outbound
This paper cites DeepSeek-V3 Technical Report.
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.379383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1f9571bd-10d7-4835-9e12-d44796c361bb · outbound
This paper cites Cross-Layer Retrospective Retrieving via Layer Attention.
Attention Residuals Cross-Layer Retrospective Retrieving via Layer Attention
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.383495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff7b1b89-f86b-40df-af12-51f254be6010 · outbound
This paper cites The Unreasonable Ineffectiveness of the Deeper Layers.
Attention Residuals The Unreasonable Ineffectiveness of the Deeper Layers
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.388399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3cf8f0c0-9401-467a-972f-e16f88b08514 · outbound
This paper cites Deep Residual Learning for Image Recognition.
Attention Residuals Deep Residual Learning for Image Recognition
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.391921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eb585261-4085-4d22-bce0-fa250a8adbe1 · outbound
This paper cites Measuring Massive Multitask Language Understanding.
Attention Residuals Measuring Massive Multitask Language Understanding
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.395547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9c275e7c-2558-4265-be01-b94e0c93a0c9 · outbound
This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.
Attention Residuals Measuring Mathematical Problem Solving With the MATH Dataset
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.399303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3c54a651-213d-47e4-b5ee-cd6e50487339 · outbound
This paper cites Training Compute-Optimal Large Language Models.
Attention Residuals Training Compute-Optimal Large Language Models
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.403147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fba6b81b-42f1-4034-9df9-f837739e9134 · outbound
This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.
Attention Residuals MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.407227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a7bd47e2-81f2-45e9-83f8-8abd564f1bfc · outbound
This paper cites Densely Connected Convolutional Networks.
Attention Residuals Densely Connected Convolutional Networks
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.410495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cbe0e777-25ac-4fbe-a9de-58ff0a209cf0 · outbound
This paper cites GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.
Attention Residuals GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.538600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e5821561-57e1-4e0d-8c4e-f08d993c508f · outbound
This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.
Attention Residuals C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.536284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2a65cd8e-770e-469f-b59c-a1a68290af71 · outbound
This paper cites Adaptive Mixtures of Local Experts.
Attention Residuals Adaptive Mixtures of Local Experts
Reference 20
- Resolution
- verified exact
- doi, observed 2026-05-21T06:39:04.353617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f43166e5-3335-48d5-9a59-31f9f092a2c4 · outbound
This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.
Attention Residuals TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.491412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cc01e81b-79f2-4d9f-bf89-8be890b07c00 · outbound
This paper cites Scaling Laws for Neural Language Models.
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.494310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b9ad86b0-945e-46b9-acdc-d45f87a2d678 · outbound
This paper cites Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention.
Attention Residuals Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.545283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5d1e8bd1-54ea-408c-8c8d-567693eb4a27 · outbound
This paper cites Depth-recurrent attention mixtures: Giving latent reasoning the attention it deserves.CoRR, abs/2601.21582.
Attention Residuals Depth-recurrent attention mixtures: Giving latent reasoning the attention it deserves.CoRR, abs/2601.21582
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.497855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a7b4be31-3d19-483a-8913-66bb55cd7d0e · outbound
This paper cites Solving Quantitative Reasoning Problems with Language Models.
Attention Residuals Solving Quantitative Reasoning Problems with Language Models
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.500945Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c1da32fa-d478-41c9-a6b0-bf01374ac6ce · outbound
This paper cites CMMLU: Measuring massive multitask language understanding in Chinese.
Attention Residuals CMMLU: Measuring massive multitask language understanding in Chinese
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.551883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3bbd3c27-48c8-4ae0-b5de-5ca19a13a636 · outbound
This paper cites SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm.
Attention Residuals SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T02:03:55.284213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9d93a0da-45d1-4a23-be1a-c0325b060e90 · outbound
This paper cites Muon is Scalable for LLM Training.
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.506714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 05bcf0ab-3cf0-47aa-b7c8-e760f495da94 · outbound
This paper cites Residual Matrix Transformers: Scaling the Size of the Residual Stream.
Attention Residuals Residual Matrix Transformers: Scaling the Size of the Residual Stream
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.510323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4c05a788-6b43-40ce-a24f-89dad17f10a4 · outbound
This paper cites LAuReL: Learned Augmented Residual Layer.
Attention Residuals LAuReL: Learned Augmented Residual Layer
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.513150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation da0a0c19-131f-4565-8cfd-6efbe6d13113 · outbound
This paper cites Online normalizer calculation for softmax.
Attention Residuals Online normalizer calculation for softmax
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.516032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2d3fe499-5d4a-4c55-b97b-fc4e3490448e · outbound
This paper cites Metalearned Neural Memory.
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.519193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 648c3699-64ee-46e6-beaf-c2a90114c946 · outbound
This paper cites an unresolved cited work.
Attention Residuals Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-05-21T06:39:04.568145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 177b40ef-d995-4946-a80f-645b9db7e617 · outbound
This paper cites Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM.
Attention Residuals Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.522153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 62c77ddd-34c1-4a51-be84-840a1cf4f093 · outbound
This paper cites Transformers without Tears: Improving the Normalization of Self- Attention.
Attention Residuals Transformers without Tears: Improving the Normalization of Self- Attention
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.572929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f926db98-2322-4bfd-bfe9-6a25db0a2e67 · outbound
This paper cites GPT-4 Technical Report.
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.524846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 752dd56c-7ae3-4437-a519-c162639bf238 · outbound
This paper cites DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging.
Attention Residuals DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.527752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 583e6877-fd89-4618-9fbd-26abe815a444 · outbound
This paper cites YaRN: Efficient Context Window Extension of Large Language Models.
Attention Residuals YaRN: Efficient Context Window Extension of Large Language Models
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.530763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 954a9af4-07f8-4c1e-a704-7f4c4e6b5e1c · outbound
This paper cites Deep Contextualized Word Representations.
Attention Residuals Deep Contextualized Word Representations
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.581686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7b535baf-9b7d-4ea7-9668-a50fe86a4abc · outbound
This paper cites Efficiently Scaling Transformer Inference.
Attention Residuals Efficiently Scaling Transformer Inference
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.533914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 256821c7-39ac-4d26-bc67-d7e1a707ad25 · outbound
This paper cites HGRN2: Gated Linear RNNs with State Expansion.
Attention Residuals HGRN2: Gated Linear RNNs with State Expansion
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.421192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 985b17a0-6dc8-433c-8422-a6ee4265ef80 · outbound
This paper cites Gpqa: A graduate-level google-proof q&a benchmark.
Attention Residuals Gpqa: A graduate-level google-proof q&a benchmark
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.547434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cbdf8d20-0202-4fb2-9969-0de1e97c3901 · outbound
This paper cites Linear Transformers Are Secretly Fast Weight Program- mers.
Attention Residuals Linear Transformers Are Secretly Fast Weight Program- mers
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.549568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 965195e4-aa19-4a49-a588-7aa1c497e067 · outbound
This paper cites Learning to control fast-weight memories: An alternative to dynamic recurrent networks.
Attention Residuals Learning to control fast-weight memories: An alternative to dynamic recurrent networks
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.555008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d4acf531-a27d-42ec-ad96-1dce1c3b7701 · outbound
This paper cites Language Models are Multilingual Chain-of-Thought Reasoners.
Attention Residuals Language Models are Multilingual Chain-of-Thought Reasoners
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.424716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7bbed93b-10a4-40fd-9dbc-821b02f4f526 · outbound
This paper cites Highway Networks.
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.427995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f7ab781d-54a3-4900-a862-35281fbb51e5 · outbound
This paper cites Learning to (Learn at Test Time): RNNs with Expressive Hidden States.
Attention Residuals Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.431481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c5abe985-4c09-4ff3-b680-94c37adb10e5 · outbound
This paper cites Retentive Network: A Successor to Transformer for Large Language Models.
Attention Residuals Retentive Network: A Successor to Transformer for Large Language Models
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.434610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 99edfd30-3825-4bce-8a83-397cf9a4e9ee · outbound
This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.
Attention Residuals Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.437729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0d64c5d0-1fda-419c-b031-6519a39c4969 · outbound
This paper cites Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study.
Attention Residuals Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.570531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 552265fb-b7c5-4cda-a845-c9aeb7553a73 · outbound
This paper cites Going deeper with Image Transformers.
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.441462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7680f6e7-6203-4138-9538-323702922807 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
Attention Residuals LLaMA: Open and Efficient Foundation Language Models
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.444807Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 37dbbe2f-d96c-4a50-ab6a-199126564810 · outbound
This paper cites Attention is All you Need.
Attention Residuals Attention is All you Need
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.579633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8185eb06-ab67-4478-afba-ba59251bccb5 · outbound
This paper cites Attention is All you Need.
Attention Residuals Attention is All you Need
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.540798Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9f5b1146-dfed-49fb-8341-7c72123b16ed · outbound
This paper cites DeepNet: Scaling Transformers to 1,000 Layers.
Attention Residuals DeepNet: Scaling Transformers to 1,000 Layers
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.447997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 618d7ae0-5c22-4467-8fe5-075080504a83 · outbound
This paper cites Mmlu-pro: A more robust and challenging multi-task language understanding benchmark.
Attention Residuals Mmlu-pro: A more robust and challenging multi-task language understanding benchmark
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.557297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b49422f5-ddb2-4966-b838-b5af57ad2b6b · outbound
This paper cites MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections.
Attention Residuals MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.559488Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9c1bd94b-8509-49bc-b6f8-44b4d8c07bcc · outbound
This paper cites Efficient Streaming Language Models with Attention Sinks.
Attention Residuals Efficient Streaming Language Models with Attention Sinks
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.450919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 72c99b56-9c08-4595-98e6-2f71d6e3ddca · outbound
This paper cites Zhihu blog post.
Attention Residuals Zhihu blog post
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.454904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2d02306a-a157-489d-985d-fd10fa1a027d · outbound
This paper cites mHC: Manifold-Constrained Hyper-Connections.
Attention Residuals mHC: Manifold-Constrained Hyper-Connections
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.458028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 185b8c26-8f61-4af6-81b0-a0a5f75ccce9 · outbound
This paper cites On Layer Normalization in the Transformer Architecture.
Attention Residuals On Layer Normalization in the Transformer Architecture
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.461102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 90ee231d-ec61-42ea-bae3-e9be4c0b5b05 · outbound
This paper cites Rope to nope and back again: A new hybrid attention strategy.
Attention Residuals Rope to nope and back again: A new hybrid attention strategy
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.465116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation da977ab6-54e8-4a60-8dab-55a3c704952a · outbound
This paper cites Gated Delta Networks: Improving Mamba2 with Delta Rule.
Attention Residuals Gated Delta Networks: Improving Mamba2 with Delta Rule
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.543086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7b5ed45f-53bc-4f59-8d87-5a8505f9ca3f · outbound
This paper cites Gated Linear Attention Transformers with Hardware-Efficient Training.
Attention Residuals Gated Linear Attention Transformers with Hardware-Efficient Training
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.561665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 817bcc4f-fba8-49c3-8aa4-19aa0201042f · outbound
This paper cites doi:10.48550/arXiv.2601.05732 , abstract =.
Attention Residuals doi:10.48550/arXiv.2601.05732 , abstract =
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.468910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6aa1181f-7725-4e87-841e-2544cb93cba1 · outbound
This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.
Attention Residuals HellaSwag: Can a Machine Really Finish Your Sentence?
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.566078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 73ffe95b-fb2e-4b31-86ca-d87450b3350d · outbound
This paper cites Root mean square layer normalization.
Attention Residuals Root mean square layer normalization
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.575153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 32d94670-4d73-4ed5-bf3a-0eca83757904 · outbound
This paper cites Deep Delta Learning.
Reference 68
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.471884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 075305c2-2607-4620-8629-cf95c7269415 · outbound
This paper cites ANCRe: Adaptive neural connection reassignment for efficient depth scaling.
Attention Residuals ANCRe: Adaptive neural connection reassignment for efficient depth scaling
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.474989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7c9cf6dc-8503-4aa4-8453-83e63a5621bf · outbound
This paper cites Kimi Linear: An Expressive, Efficient Attention Architecture.
Attention Residuals Kimi Linear: An Expressive, Efficient Attention Architecture
Reference 70
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T06:39:04.478018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2bb513d6-b13d-4e65-b9ec-b5a473f04874 · outbound
This paper cites Understanding Transformer from the Perspective of Associative Memory.
Attention Residuals Understanding Transformer from the Perspective of Associative Memory
Reference 71
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.482086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 728ac2f4-4b23-4422-994b-e2f95267e667 · outbound
This paper cites Value Residual Learning.
Attention Residuals Value Residual Learning
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T06:39:04.577609Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ac404945-6750-43ee-8dd7-df19403f4fb4 · outbound
This paper cites Hyper-Connections.
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.485046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4a200686-d93c-4cbe-84b0-d98ab9b9c9ea · outbound
This paper cites an unresolved cited work.
Attention Residuals Unresolved cited work
Reference 74
- Resolution
- unresolved
- raw_fallback, observed 2026-05-21T06:39:04.563688Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f45a50d7-407e-49fa-b27e-4c577da0d402 · outbound
This paper cites HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization.
Attention Residuals HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.488346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation c10814fc-5120-4d89-b839-83788e6180bd · inbound
Gradient Boosting within a Single Attention Layer cites this paper.
Gradient Boosting within a Single Attention Layer Attention Residuals
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7c0a0642-7095-49c8-9ede-11240286477b · inbound
XAttnRes: Cross-Stage Attention Residuals for Medical Image Segmentation cites this paper.
XAttnRes: Cross-Stage Attention Residuals for Medical Image Segmentation Attention Residuals
Reference 30
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7cc6aa49-8b05-4c51-80d2-a08f42c68219 · inbound
Symbolic-Vector Attention Fusion for Collective Intelligence cites this paper.
Symbolic-Vector Attention Fusion for Collective Intelligence Attention Residuals
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T11:46:35.757645Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5707d348-5794-4cb8-bf38-5e6e9bcb18a6 · inbound
CAWN: Continuous Acoustic Wave Networks for Autoregressive Language Modeling cites this paper.
CAWN: Continuous Acoustic Wave Networks for Autoregressive Language Modeling Attention Residuals
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T10:31:11.574398Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00f470b5-475e-4dbf-9742-16ccf21ff715 · inbound
DALM: A Domain-Algebraic Language Model via Three-Phase Structured Generation cites this paper.
DALM: A Domain-Algebraic Language Model via Three-Phase Structured Generation Attention Residuals
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 72ec83d9-8ad3-4191-8b0b-79091258bd26 · inbound
Hyperloop Transformers cites this paper.
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 67c4b4fc-fc44-44f7-912c-eb4cb51e43d8 · inbound
A Cellular Doctrine of Morality: Intrinsic Active Precision and the Mind-Reality Overload Dilemma cites this paper.
A Cellular Doctrine of Morality: Intrinsic Active Precision and the Mind-Reality Overload Dilemma Attention Residuals
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f23cbd4b-2acd-40fb-9810-39910ab9ae77 · inbound
Transformers with Selective Access to Early Representations cites this paper.
Transformers with Selective Access to Early Representations Attention Residuals
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eff4cbb6-4a3e-4c85-bb36-78f90b227c87 · inbound
Transformers with Selective Access to Early Representations cites this paper.
Transformers with Selective Access to Early Representations Attention Residuals
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 030ccf04-6ec5-451e-a95b-8369a8fca9d5 · inbound
BARFI-Q: Quantum-Enhanced Block Attention Residual Fusion Framework for Multivariate Time-Series Forecasting in Atom Interferometry cites this paper.
BARFI-Q: Quantum-Enhanced Block Attention Residual Fusion Framework for Multivariate Time-Series Forecasting in Atom Interferometry Attention Residuals
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0dd98c88-209c-4282-b0e1-c2d561e7b124 · inbound
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps cites this paper.
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps Attention Residuals
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cb90e315-dc66-41e1-bf93-66a615c8c60b · inbound
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps cites this paper.
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps Attention Residuals
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 15a0b7b6-bb29-4afb-b2f1-539669c54ba1 · inbound
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps cites this paper.
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps Attention Residuals
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation abb3668b-bb59-4bc0-b692-1def4b362237 · inbound
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps cites this paper.
NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps Attention Residuals
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T23:25:07.733791Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 257c9278-1dab-47d9-a00e-09aab3f41368 · inbound
Cubit: Token Mixer with Kernel Ridge Regression cites this paper.
Cubit: Token Mixer with Kernel Ridge Regression Attention Residuals
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 952ccb53-69f2-43d9-a6c4-4079a02d0cc9 · inbound
Cubit: Token Mixer with Kernel Ridge Regression cites this paper.
Cubit: Token Mixer with Kernel Ridge Regression Attention Residuals
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 61df5385-2b6e-4b84-9ea8-4b283da93d0d · inbound
When Does Value-Aware KV Eviction Help? A Fixed-Contract Diagnostic for Non-Monotone Cache Compression cites this paper.
When Does Value-Aware KV Eviction Help? A Fixed-Contract Diagnostic for Non-Monotone Cache Compression Attention Residuals
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bd770621-b7ab-4906-b503-cd89b44247af · inbound
Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms cites this paper.
Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms Attention Residuals
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation de495717-7d47-4ca6-bc1a-68113a868ea6 · inbound
L2A: Learning to Accumulate Pose History for Accurate 3D Human Pose Estimation cites this paper.
L2A: Learning to Accumulate Pose History for Accurate 3D Human Pose Estimation Attention Residuals
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 46c8beb2-6ace-4b6e-a5bf-1ced0d8c57d9 · inbound
L2A: Learning to Accumulate Pose History for Accurate 3D Human Pose Estimation cites this paper.
L2A: Learning to Accumulate Pose History for Accurate 3D Human Pose Estimation Attention Residuals
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7eb30562-3fc6-4402-8f3f-02245e83f7b2 · inbound
RigidFormer: Learning Rigid Dynamics using Transformers cites this paper.
RigidFormer: Learning Rigid Dynamics using Transformers Attention Residuals
Reference 20
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1c9b20d8-3669-486f-a094-0ab4d07a05c8 · inbound
Attention Drift: What Autoregressive Speculative Decoding Models Learn cites this paper.
Attention Drift: What Autoregressive Speculative Decoding Models Learn Attention Residuals
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c4251de7-1817-4176-80a0-0f497771c026 · inbound
LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models cites this paper.
LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models Attention Residuals
Reference 72
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1c46ef78-db00-4907-9aea-0aa11011825b · inbound
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models Attention Residuals
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9d712c1f-6f9c-4c16-9dd3-93ba990c25ac · inbound
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models Attention Residuals
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2e67ee28-9c86-4962-8d63-9724d2eb1219 · inbound
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.
Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models Attention Residuals
Reference 22
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T08:04:02.643856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9ef6ed24-fbce-4efd-9698-acf9f77f0782 · inbound
RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably cites this paper.
RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably Attention Residuals
Reference 40
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 621d9bdd-1780-4161-90ea-c36599257c45 · inbound
Attention Sinks and Outliers in Attention Residuals cites this paper.
Attention Sinks and Outliers in Attention Residuals Attention Residuals
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9219be97-0eaa-4668-813a-dce777a30f0b · inbound
Delta Attention Residuals cites this paper.
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 82539a73-f1a1-4285-a021-fedc949d7f9d · inbound
Rethinking Cross-Layer Information Routing in Diffusion Transformers cites this paper.
Rethinking Cross-Layer Information Routing in Diffusion Transformers Attention Residuals
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e84bdd41-b878-4042-a520-1ee7241d5b8f · inbound
Rethinking Cross-Layer Information Routing in Diffusion Transformers cites this paper.
Rethinking Cross-Layer Information Routing in Diffusion Transformers Attention Residuals
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T17:54:57.929350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c7cdbabd-233f-45ff-8e08-9efbf41bcddb · inbound
Most Transformer Modifications Still Do Not Transfer at 1-3B: A 2020-2026 Update to Narang et al. (2021) with Downstream Evaluation and a Noise Floor cites this paper.
Most Transformer Modifications Still Do Not Transfer at 1-3B: A 2020-2026 Update to Narang et al. (2021) with Downstream Evaluation and a Noise Floor Attention Residuals
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:39:04.582456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4efe9a48-8743-4e08-898c-bffdaa527ebd · inbound
Multi-Gate Residuals cites this paper.
Reference 13
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-25T04:50:20.366098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2b6441e2-1733-4700-b1bc-86a5ad3a9f4d · inbound
Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis cites this paper.
Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis Attention Residuals
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T22:34:02.164157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e491433f-a1ca-4ed9-9b7e-dc546b46bf81 · inbound
PowLU: An Activation Function for Stable Pre-Training of LLMs cites this paper.
PowLU: An Activation Function for Stable Pre-Training of LLMs Attention Residuals
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T21:53:59.435252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation afe420c4-4786-4d39-a94b-9f1e54565cb2 · inbound
Meta-Attention: Bayesian Per-Token Routing for Efficient Transformer Inference cites this paper.
Meta-Attention: Bayesian Per-Token Routing for Efficient Transformer Inference Attention Residuals
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T14:53:31.440246Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0404ab68-b90f-4392-be4f-dbf383816540 · inbound
Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics cites this paper.
Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics Attention Residuals
Reference 48
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T09:13:16.369635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7657c6ec-a4f5-42c3-99bc-9d24218f16f2 · inbound
Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.
Do Value Vectors in Deep Layers Need Context from the Residual Stream? Attention Residuals
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T23:16:23.393310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ea5ed3be-83a3-4e99-8d8f-ed8f5f91111f · inbound
Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.
Do Value Vectors in Deep Layers Need Context from the Residual Stream? Attention Residuals
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:41:21.055096Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e81a4f83-eff6-4946-bf0b-ed4ea8637247 · inbound
RowNet: A Memory Transformer for Tabular Regression cites this paper.
RowNet: A Memory Transformer for Tabular Regression Attention Residuals
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T06:56:44.711940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 221b1ff3-3f91-41a2-b9cf-6d71cc359f08 · inbound
Depth-Attention: Cross-Layer Value Mixing for Language Models cites this paper.
Depth-Attention: Cross-Layer Value Mixing for Language Models Attention Residuals
Reference 11
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T08:36:48.492882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dfba7ea8-a132-444a-9d29-691d2e009aae · inbound
HAARES Half-Split Residual Basis Routing for Deep Transformers cites this paper.
HAARES Half-Split Residual Basis Routing for Deep Transformers Attention Residuals
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T11:36:55.418977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f26a50ab-71bd-476f-9e2d-18de8415f6fd · inbound
DeRes: Decoupling Residual Stability and Adaptivity for Scalable CTR Prediction cites this paper.
DeRes: Decoupling Residual Stability and Adaptivity for Scalable CTR Prediction Attention Residuals
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T21:57:25.811326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ea5a36e1-cc8a-46e7-87dc-23c50209f99a · inbound
DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning cites this paper.
DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning Attention Residuals
Reference 25
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T20:47:23.055792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 48a47edb-8808-42dd-89c4-f8b7ca3901ae · inbound
Variable-Width Transformers cites this paper.
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T20:58:58.601724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0af3eaa5-f195-4700-ba68-f74e05297c00 · inbound
All Routes Lead to Collapse cites this paper.
Reference 9
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T08:39:42.444991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation db5a468d-17d8-4d64-9199-138877cb7e7e · inbound
Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients cites this paper.
Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients Attention Residuals
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T17:20:00.906151Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d7841a03-dc36-49cb-b249-c590b944bc46 · inbound
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems cites this paper.
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems Attention Residuals
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T14:59:55.453169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c400cd70-cbc7-4eaf-ba85-00f9d0a1e57b · inbound
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems cites this paper.
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems Attention Residuals
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T18:43:51.173056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 187bf93e-c3e0-48c2-9dc4-d1d6db4e16c3 · inbound
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems cites this paper.
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems Attention Residuals
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:04:09.464805Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9649c61-ea17-4f2d-b179-295f764b3bd8 · inbound
Mechanism-Driven Monitors for Preemptive Detection of LLM Training Instability cites this paper.
Mechanism-Driven Monitors for Preemptive Detection of LLM Training Instability Attention Residuals
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T17:15:50.562998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c2768088-cf49-4618-ae8a-4de1e55e6b49 · inbound
Review Residuals: Update-Conditioned Residual Gating for Transformers cites this paper.
Review Residuals: Update-Conditioned Residual Gating for Transformers Attention Residuals
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T06:45:29.870361Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ab8fea19-ddf3-436f-b3e2-e544993e1d48 · inbound
Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.
Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers Attention Residuals
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T13:03:39.236118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9485afba-2355-4535-b4ed-09cec240ec37 · inbound
Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.
Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers Attention Residuals
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T16:21:05.570023Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8aab5da6-f6fe-40f9-ba9b-85a8fabd0508 · inbound
Linear Attention Architectures: Mechanisms, Trade-offs, and Cross-Layer Routing cites this paper.
Linear Attention Architectures: Mechanisms, Trade-offs, and Cross-Layer Routing Attention Residuals
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T14:57:14.485595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bd9cdf6b-2d0b-4013-b5c8-9889a457b6f1 · inbound
Structural Bottlenecks on Frequency Representation in End-to-End Audio Models cites this paper.
Structural Bottlenecks on Frequency Representation in End-to-End Audio Models Attention Residuals
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T05:46:50.396849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf92659f-fb94-48bf-802b-07593fadec71 · inbound
Low-Rank Attention Residuals cites this paper.
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T17:37:51.504123Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation daa1b5dd-535e-4667-a329-e4f6578046fb · inbound
xHC: Expanded Hyper-Connections cites this paper.
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T01:53:17.306868Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a5f1240-2c4a-4bc0-b1a2-64068c2353d8 · inbound
A Controlled Study of Attention-Only Transformers cites this paper.
A Controlled Study of Attention-Only Transformers Attention Residuals
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T16:19:08.171765Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6de9292-5daf-48eb-89fd-f0a142ac9f1b · inbound
Dual Attention Residuals cites this paper.
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T14:36:36.160565Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 022e5892-adbc-4a92-9637-75959bf95652 · inbound
SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation cites this paper.
SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation Attention Residuals
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T07:09:05.956746Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 234cd3f0-8fc0-4355-8d8b-edae69b2f58d · inbound
Dynamic Commonsense Coordination for Empathetic Response Generation cites this paper.
Dynamic Commonsense Coordination for Empathetic Response Generation Attention Residuals
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T05:43:51.525154Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 884647fb-dbc4-4bee-86c7-a51580a41cd6 · inbound
Bridging Compute- and Data-Optimal Pretraining cites this paper.
Bridging Compute- and Data-Optimal Pretraining Attention Residuals
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T03:02:01.365825Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation abada9b0-c345-401e-81c2-4b4ba4b46d68 · inbound
Multi-Head Attention Residuals cites this paper.
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T11:39:22.850069Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd5aa1d8-db5a-42db-a10d-2648fef6ea78 · inbound
Multi-Head Attention Residuals cites this paper.
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T01:39:47.872763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.