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Paper Citation Record · LEDGER

Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.03735.

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

pith.paper-citation-record.v1
2410.03735 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:04:22.901349Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:15:58.988295Z

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 4514bdcb-4843-496a-b304-2ba5fc63bd0c · inbound

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining cites this paper.

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:04:22.901349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:04:22.901349Z digest=sha256:4e1be459b25c2b92bd9835a8344ec41b7ac4cd51f8b7fb82844b6717745ca2ae

Observation 74951000-d1e7-44b6-bd03-72c9a584ee1f · inbound

Assessing the Role of Data Quality in Training Bilingual Language Models cites this paper.

Assessing the Role of Data Quality in Training Bilingual Language Models Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:57.732570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:42:57.732570Z digest=sha256:0628ec2384f85ccd1cb5e868a542212de98c2db891e508690341f5c0face84a9

Observation 14fd87ce-5af6-49d7-b84b-84a018c74bc3 · inbound

Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.

Language Models Improve When Pretraining Data Matches Target Tasks Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T16:53:10.133518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:53:10.133518Z digest=sha256:e1cf9f868806e7344ce75bf4aec6c1a6b4157024b9ed9da83fe2147a85f5e691

Observation c1f66cfd-4456-4ec6-a630-ddb72b9ecda1 · inbound

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining cites this paper.

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T13:24:14.800183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:24:14.800183Z digest=sha256:be3dfce2ce532b8c017cbfbd0a897a9203aa8b1051ace25f08d7d94b4ce15e7a

Observation 7feaa412-33a7-44f7-a1d9-a6d5bbc3e356 · inbound

Multi-Task GRPO: Reliable LLM Reasoning Across Tasks cites this paper.

Multi-Task GRPO: Reliable LLM Reasoning Across Tasks Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-03T04:17:27.132962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:17:27.132962Z digest=sha256:15e48a456bb62e86f709ef5d56cc8a1225c58671e7350240b6f44f853f077452

Observation c2274be3-db88-4413-88b3-69a1ca1e5520 · inbound

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:58.990203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T17:42:31.465077Z digest=sha256:3129a63949fdb14857879687ad5ffac2966ed13323bd79fccb24146392e216df