Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-12T03:33:45.192139Z
Paper Citation Record · LEDGER
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization
As of 5 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2605.08809.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact13
- verified fuzzy3
- unresolved3
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b0e0be72-5092-499a-9868-616165665746 · outbound
This paper cites Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:16:28.852066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 54955a1a-11ae-4f2a-9434-07f95f53ab40 · outbound
This paper cites Joint selection for large-scale pre-training data via policy gradient-based mask learning.arXiv preprint arXiv:2512.24265.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Joint selection for large-scale pre-training data via policy gradient-based mask learning.arXiv preprint arXiv:2512.24265
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:16:28.903351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1db87a18-273a-4772-87e1-aa024fc05650 · outbound
This paper cites He, B., Yin, L., Zhen, H.-L., Liu, S., Wu, H., Zhang, X., Yuan, M., and Ma, C.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization He, B., Yin, L., Zhen, H.-L., Liu, S., Wu, H., Zhang, X., Yuan, M., and Ma, C
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:16:28.917670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 97faa1aa-aee3-4e3f-a323-d6b70a290b16 · outbound
This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization SimCSE: Simple Contrastive Learning of Sentence Embeddings
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T07:48:23.738089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8a831358-8906-4b57-a731-761465cacc49 · outbound
This paper cites Jun Hu, Wenwen Xia, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, and Jun Zhou.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Jun Hu, Wenwen Xia, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, and Jun Zhou
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:11:48.180033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8e02469a-04b3-4fc2-ac2e-a3023d04441a · outbound
This paper cites Mixtral of Experts.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Mixtral of Experts
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T07:16:28.913257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f2855f91-1f3f-48db-b801-98d481d39e39 · outbound
This paper cites A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models
Reference 7
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:16:28.897313Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d09df841-1e59-46a7-9b1c-7307c3208f27 · outbound
This paper cites Text and Code Embeddings by Contrastive Pre-Training.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Text and Code Embeddings by Contrastive Pre-Training
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:24:12.120554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ffe8bed3-18da-4e29-8c19-9f7169094d3a · outbound
This paper cites Representation Learning with Contrastive Predictive Coding.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Representation Learning with Contrastive Predictive Coding
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T07:16:28.820669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 61134f1e-7314-4cdf-ad7e-aa4ece46efe2 · outbound
This paper cites GLU Variants Improve Transformer.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization GLU Variants Improve Transformer
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T07:16:28.892187Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9e249d79-f9f5-475d-98a4-ed5441191f7c · outbound
This paper cites A simple contrastive learning framework for interactive argument pair identification via argument-context extraction.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization A simple contrastive learning framework for interactive argument pair identification via argument-context extraction
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:11:48.184269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1018947d-9799-41ad-96ba-0ab476a704d6 · outbound
This paper cites MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T01:54:43.618312Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f2e5d0f5-5471-49db-8328-91c0c4e4ecad · outbound
This paper cites LLMs are Also Effective Embedding Models: An In-depth Overview.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization LLMs are Also Effective Embedding Models: An In-depth Overview
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:16:28.880514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 85cc35bc-1a59-4504-b3bd-f1b842046675 · outbound
This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T07:16:28.863749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 808990e5-6e2e-493a-889d-8d20a7c105c5 · outbound
This paper cites AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:12.038297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e1f8b234-50ae-4a35-a057-d5b760ef3c42 · outbound
This paper cites Do Generated Data Always Help Contrastive Learning?.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Do Generated Data Always Help Contrastive Learning?
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:16:28.838582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 688420ce-fd93-446a-ae48-f658e60628ec · outbound
This paper cites Is contrastive learning necessary? a study of data augmentation vs contrastive learning in sequential recommen- dation.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Is contrastive learning necessary? a study of data augmentation vs contrastive learning in sequential recommen- dation
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T19:11:48.188493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e7fab80f-0bf7-4832-9f40-e7fadc40ed2c · outbound
This paper cites an unresolved cited work.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:11:48.211340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 740bbdbc-b5ea-4b88-ba79-11c904593bca · outbound
This paper cites an unresolved cited work.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Unresolved cited work
Reference 19
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:11:48.192602Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3e4bed0a-3173-4bd3-8da4-40e5dfdcdd75 · outbound
This paper cites an unresolved cited work.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T19:11:48.196449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e97ad2c6-7ff8-4069-af58-49c27bc94206 · outbound
This paper cites an unresolved cited work.
SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization Unresolved cited work
Reference 21
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-12T19:11:48.207258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
No inbound Pith citation observations are available.