Pith. sign in

Paper Citation Record · LEDGER

SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2207.02578.

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

pith.paper-citation-record.v1
2207.02578 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:59:01.972866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T13:24:32.151302Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1babce6f-48cb-4d74-9b81-61da0ef5bdf8 · inbound

Text Embeddings by Weakly-Supervised Contrastive Pre-training cites this paper.

Text Embeddings by Weakly-Supervised Contrastive Pre-training SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:54:03.973111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-11T04:54:03.524365Z digest=sha256:79841b907f137aea0a0744c1eedf4b04956aa2130be6ac64ed3cd3f59152ba61

Observation 97e0c20e-f37c-4282-a2fe-c18e3703a70e · inbound

C-Pack: Packed Resources For General Chinese Embeddings cites this paper.

C-Pack: Packed Resources For General Chinese Embeddings SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-13T13:24:32.153132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-13T13:24:32.084878Z digest=sha256:796ff1682743c123400bc78f4083828eb6c99ac19c93d162bdeffa2da4bd5848

Observation c1e546b4-445b-497b-9862-7a311a29bbc0 · inbound

LLMs are Also Effective Embedding Models: An In-depth Overview cites this paper.

LLMs are Also Effective Embedding Models: An In-depth Overview SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T13:59:01.972866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:59:01.972866Z digest=sha256:130f906e6e90631bfefa8ad54e3672b99bb0d41030071640db9a25a54fafcbcc

Observation d45be8e3-0179-43c7-9a6d-4a209f28ba9d · inbound

AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark cites this paper.

AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T13:29:25.259968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:29:25.259968Z digest=sha256:080cdc1511b4dbb6a301474b81aa97d71b0b8fb85723f830ac4fd3c2b8d60f61

Observation 682c7332-6f17-4227-901e-ce506be06262 · inbound

State Space Models are Strong Text Rerankers cites this paper.

State Space Models are Strong Text Rerankers SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-11T12:22:28.522045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:22:28.522045Z digest=sha256:08aaf80524799a7a1ca8a937d8dd7c8c37f2dffb2fb4973d5267f2e2cc0943bf

Observation 26f40899-5638-47f2-8905-a99029527880 · inbound

Matryoshka Re-Ranker: A Flexible Re-Ranking Architecture With Configurable Depth and Width cites this paper.

Matryoshka Re-Ranker: A Flexible Re-Ranking Architecture With Configurable Depth and Width SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T13:37:35.412566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T13:37:35.412566Z digest=sha256:9b7c839250e7ecf5e24a311498eeef468787ea24d1db2efde23c0168eeb32d96

Observation f1e384ce-7fc5-4fcd-8409-2c06e3cde6aa · inbound

O1 Embedder: Let Retrievers Think Before Action cites this paper.

O1 Embedder: Let Retrievers Think Before Action SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T12:25:12.372217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:25:12.372217Z digest=sha256:6622c0f31b8e420a4325d2388438555392edc1cba139d924429ed646c5ff885e

Observation 92af16bc-462a-4ebc-9bdc-690ba6ce0fee · inbound

RaDeR: Reasoning-aware Dense Retrieval Models cites this paper.

RaDeR: Reasoning-aware Dense Retrieval Models SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:35:19.953507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:19.953507Z digest=sha256:be793bd2b19fe0d176939d7705f843c338ec67e0419bdcfde1e7f753c564a098

Observation 2d0f436b-e6f4-46e0-9e1d-5dc37c9445b2 · inbound

Exp4Fuse: A Rank Fusion Framework for Enhanced Sparse Retrieval using Large Language Model-based Query Expansion cites this paper.

Exp4Fuse: A Rank Fusion Framework for Enhanced Sparse Retrieval using Large Language Model-based Query Expansion SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:18.768905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:18.768905Z digest=sha256:e0ea5fa3ac97747511b75ca02826115fd94c332cb44bd43036b53b6bbcd708df

Observation 24d3bc36-5d57-4355-b0dc-07a41c16901d · inbound

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval cites this paper.

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T10:40:14.712740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:40:14.712740Z digest=sha256:809bb5b17d03b7c4c727ba383bebc0ba197de0d1a9bc8a0e336c918620c1ddcd