Paper Citation Record · LEDGER

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer

As of 23 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.05937.

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

pith.paper-citation-record.v1
2607.05937 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T20:07:20.682401Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

verified exact3
verified fuzzy19
unresolved1
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a52716c8-d377-4f85-b9fa-cbcece6937e5 · outbound

This paper cites FinBERT: Financial Sentiment Analysis with Pre-trained Language Models.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer FinBERT: Financial Sentiment Analysis with Pre-trained Language Models

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:15:34.389927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad7e9b29-9264-4984-973e-6d30297f0242 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:15:34.392426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fde67741-4fe0-4c9a-8cad-1b764696744d · outbound

This paper cites How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.008918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3df4edf-c9c0-4599-a855-d9ad7b70296f · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Manning, Andrew Ng, and Christopher Potts

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.007152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8c384d16-f308-4460-8a95-f9e4c05f8001 · outbound

This paper cites Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts.Journal of the Association for Information Science and Technology, 65(4):782–796, 2014.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts.Journal of the Association for Information Science and Technology, 65(4):782–796, 2014

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.010715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3e23986-57a1-4e34-be6a-95b22bd538ee · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:15:34.387412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 66819d25-fa68-45e9-a3c2-486d2d8bf48d · outbound

This paper cites Domain-Adversarial Training of Neural Networks.J.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Domain-Adversarial Training of Neural Networks.J

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.012423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8b9d926d-4f4a-4954-9df0-3b663bbd705b · outbound

This paper cites Borgwardt, Malte J.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Borgwardt, Malte J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.014045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6efb964c-e25a-46fe-b840-d509114e80ba · outbound

This paper cites Supervised Contrastive Learning.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Supervised Contrastive Learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.005457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bebb83d9-3a2d-4e46-a850-f31c92427dc2 · outbound

This paper cites Character- level Convolutional Networks for Text Classification.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Character- level Convolutional Networks for Text Classification

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.000367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b180c4ab-5bca-4e6a-9eb4-9e5589d82f23 · outbound

This paper cites Hidden Factors and Hidden Topics: Understanding Rating Dimensions with ReviewText.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Hidden Factors and Hidden Topics: Understanding Rating Dimensions with ReviewText

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.996918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ee935ff3-754b-4869-ad9b-63b768761c91 · outbound

This paper cites an unresolved cited work.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-07-08T20:15:34.993267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9896fe34-fd2e-46eb-a07e-5b814329477c · outbound

This paper cites BERT Re- discovers the Classical NLP Pipeline.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer BERT Re- discovers the Classical NLP Pipeline

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.991667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 43e6b3bf-123b-497f-a4d8-8a71558ddb09 · outbound

This paper cites Benchmark Probing: Inves- tigating Data Leakage in Large Language Models.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Benchmark Probing: Inves- tigating Data Leakage in Large Language Models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.990000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 76d43276-56d5-495d-aeb8-66feafd128bb · outbound

This paper cites Benchmarkdatacontaminationoflargelanguage models: A survey, 2024.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Benchmarkdatacontaminationoflargelanguage models: A survey, 2024

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.995112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 79381513-efb0-4be3-b625-23450860cd4f · outbound

This paper cites The Emperor’s New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer The Emperor’s New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.998667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b5c8b15e-393f-413a-aa1d-7a23487fe9ae · outbound

This paper cites Neural Unsupervised Domain Adaptation in NLP—A Survey.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Neural Unsupervised Domain Adaptation in NLP—A Survey

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.002064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 82a2abc2-6429-4e3c-b448-f64638b38eb6 · outbound

This paper cites Rethink Maximum Mean Discrepancy for Domain Adap- tation, 2020.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Rethink Maximum Mean Discrepancy for Domain Adap- tation, 2020

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.988272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea7e0d52-1fa2-4714-98cc-2e339001530d · outbound

This paper cites Freeze the Backbones: a Parameter-Efficient ContrastiveApproachtoRobustMedicalVision-Language Pre-Training.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Freeze the Backbones: a Parameter-Efficient ContrastiveApproachtoRobustMedicalVision-Language Pre-Training

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.003880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9662bf10-15cb-447b-8a20-3480719fecc7 · outbound

This paper cites No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:35.015760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e0d816c4-7056-490e-ab83-eec9ebaeead3 · outbound

This paper cites Domain Adversarial Training for Aspect-Based Sentiment Analysis.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Domain Adversarial Training for Aspect-Based Sentiment Analysis

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.986467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fdeac4cf-5459-4262-bb26-5e4c6f33ef21 · outbound

This paper cites Pseudo-Label Guided Unsupervised Domain Adaptation of Contextual Embeddings.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Pseudo-Label Guided Unsupervised Domain Adaptation of Contextual Embeddings

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.984724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ef085e52-3718-4553-a25e-fb4c8e682f75 · outbound

This paper cites Decoupledweightdecay regularization, 2019.

Is Domain Adaptation Always Helpful? A Frozen-Backbone Study of Cross-Domain Sentiment Transfer Decoupledweightdecay regularization, 2019

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:15:34.982962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.