Paper Citation Record · LEDGER

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning

As of 12 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2412.09046.

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

pith.paper-citation-record.v1
2412.09046 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:25:50.708524Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:04:40.117223Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T15:04:40.414544Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy42
unresolved5
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80f00e39-057c-44ff-986e-bdf8a3f83944 · outbound

This paper cites Knowing what, how and why: A near complete solution for aspect-based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Knowing what, how and why: A near complete solution for aspect-based sentiment analysis,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.099405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c5831fd6-91b1-4aea-a4df-1e0e9575701b · outbound

This paper cites A survey on aspect- based sentiment analysis: Tasks, methods, and challenges,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A survey on aspect- based sentiment analysis: Tasks, methods, and challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.092132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b2374658-9292-4981-a34f-c1612cc6183a · outbound

This paper cites Learning implicit sentiment in aspect-based sentiment analysis with supervised contrastive pre-training,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Learning implicit sentiment in aspect-based sentiment analysis with supervised contrastive pre-training,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.084182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fe9ffa00-a5dd-42d5-9472-abd51a6e7bf9 · outbound

This paper cites Sentiment analysis in the era of large language models: A reality check,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Sentiment analysis in the era of large language models: A reality check,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.076126Z

Source-reported events for the cited work

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Observation 1c1147a0-6eed-497c-92a4-c1209d6c0b84 · outbound

This paper cites Affective computing in the era of large language models: A survey from the nlp perspective,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Affective computing in the era of large language models: A survey from the nlp perspective,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.068183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b53e8edc-a8fa-4dd2-a191-42838e05f352 · outbound

This paper cites Reasoning implicit sentiment with chain-of-thought prompting,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Reasoning implicit sentiment with chain-of-thought prompting,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.060492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 531c4a86-18a4-411c-9b45-71f78f2c3253 · outbound

This paper cites Emergent abilities of large language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Emergent abilities of large language models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.053395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d3ec52f2-6044-4c7a-86df-db275b02f2c8 · outbound

This paper cites Siren’s song in the ai ocean: A survey on hallucination in large language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Siren’s song in the ai ocean: A survey on hallucination in large language models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.046057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 447a0c26-97e1-446c-8911-9fa0f946af41 · outbound

This paper cites A survey on the honesty of large language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A survey on the honesty of large language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.038875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 52e775f0-6f41-4833-98d2-ff720274257f · outbound

This paper cites A unified architecture for natural language processing: deep neural networks with multitask learning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A unified architecture for natural language processing: deep neural networks with multitask learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.030587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 253a983f-79a9-4517-a1fb-9cda7a0a7e16 · outbound

This paper cites A survey of multi-task learning in natural language processing: Regarding task relatedness and training methods,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A survey of multi-task learning in natural language processing: Regarding task relatedness and training methods,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.022136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 931afaf8-19df-47ae-b46d-83286a8b8bd4 · outbound

This paper cites Large language models are reasoning teachers,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Large language models are reasoning teachers,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.013720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6e53ac43-d240-4aac-9bd5-8760a1621709 · outbound

This paper cites Explanations from large language models make small reasoners better,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Explanations from large language models make small reasoners better,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:51.005187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b30db37c-65ed-4b34-93a1-55c5095c5fcc · outbound

This paper cites Semeval-2015 task 9: Clipeval implicit polarity of events,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Semeval-2015 task 9: Clipeval implicit polarity of events,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.996956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9a288ea7-bb37-4e2c-bb9c-6d473ac69fde · outbound

This paper cites Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.988810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e5ba2df8-3cbc-4030-8bdd-39cff914a663 · outbound

This paper cites an unresolved cited work.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:25:50.981270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6a645e2b-508d-4f71-873f-1090a6803611 · outbound

This paper cites KC-ISA: An implicit sentiment analysis model combining knowledge enhancement and context features,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning KC-ISA: An implicit sentiment analysis model combining knowledge enhancement and context features,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.972599Z

Source-reported events for the cited work

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Observation f84f9b89-9dd4-4b2e-a52e-1d5849a2d808 · outbound

This paper cites Implicit sentiment analysis with event-centered text representation,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Implicit sentiment analysis with event-centered text representation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.964051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 93c28d47-c5e2-484b-8578-056a281abe57 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 19

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Source-reported events for the cited work

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Observation c41ee714-9a4c-4b5a-a6eb-2eb9d5155dec · outbound

This paper cites A contrastive cross-channel data augmentation framework for aspect-based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A contrastive cross-channel data augmentation framework for aspect-based sentiment analysis,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.949017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e29a88a-047b-4df2-920e-fed01c5b0f90 · outbound

This paper cites Relational graph attention network for aspect-based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Relational graph attention network for aspect-based sentiment analysis,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.940523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6ebdd096-ba29-47df-a38d-5820be9efacf · outbound

This paper cites Causal intervention improves implicit sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Causal intervention improves implicit sentiment analysis,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.932966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8a7a41b4-1b61-43c1-ae41-1ebd780f2997 · outbound

This paper cites Aspect- based sentiment analysis with explicit sentiment augmentations,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Aspect- based sentiment analysis with explicit sentiment augmentations,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.924759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 790d20e9-8182-4faf-a8c7-37ba77dc0081 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Self-refine: Iterative refinement with self-feedback,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.916928Z

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Observation 06537626-d4e7-494f-97ae-87d848b59436 · outbound

This paper cites Multitask learning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Multitask learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.909140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d5a58b9e-1b87-4902-bf6e-b60743dd9af6 · outbound

This paper cites Multi-task bert for aspect-based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Multi-task bert for aspect-based sentiment analysis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.900980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 599397e2-affb-48a6-8e0c-097517fd8d67 · outbound

This paper cites Joint aspect and polarity classification for aspect-based sentiment analysis with end-to- end neural networks,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Joint aspect and polarity classification for aspect-based sentiment analysis with end-to- end neural networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.893066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7964e3dc-bbbd-4497-9a05-6553dd46a77b · outbound

This paper cites A multi-task learning model for chinese-oriented aspect polarity classification and aspect term extraction,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning A multi-task learning model for chinese-oriented aspect polarity classification and aspect term extraction,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.883780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b3ebfa9-a21b-4223-9a75-a819848b95f0 · outbound

This paper cites Aspect-based sentiment analysis with multi-task learning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Aspect-based sentiment analysis with multi-task learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.874311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 010c927c-2368-422f-b8e8-8f92ccf7f0bf · outbound

This paper cites Aspect-based sentiment analysis via multitask learning for online reviews,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Aspect-based sentiment analysis via multitask learning for online reviews,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.866373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 53df9d5b-faf6-4755-9661-c307d1354daa · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.858521Z

Source-reported events for the cited work

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Observation d53036b4-0e1b-41c3-adcf-53c1b554d514 · outbound

This paper cites Unifiedabsa: A unified absa framework based on multi-task instruction tuning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Unifiedabsa: A unified absa framework based on multi-task instruction tuning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.849974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 552876df-b5c9-43b4-9d64-76c27bc934db · outbound

This paper cites Mvp: Multi-view prompting improves aspect sentiment tuple prediction,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Mvp: Multi-view prompting improves aspect sentiment tuple prediction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.841521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7cf70022-eb86-4ffa-b551-b4e99425bf8d · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Chain-of-thought prompting elicits reasoning in large language models,

Reference 34

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Source-reported events for the cited work

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Observation 1efca18d-7b2a-4094-a6df-6d423dd0014e · outbound

This paper cites Large language models are zero-shot reasoners,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Large language models are zero-shot reasoners,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.828061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d02f9f5d-1da7-4370-8ac7-346c4a821c17 · outbound

This paper cites Language models are few-shot learners,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Language models are few-shot learners,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T17:25:50.679619Z

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Observation f028e5f4-cab6-407b-9ce7-d250aebfe7e8 · outbound

This paper cites Complexity-based prompting for multi-step reasoning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Complexity-based prompting for multi-step reasoning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.813804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1414d7ce-5fea-47f2-8a33-c4c801a498a1 · outbound

This paper cites Automatic chain of thought prompting in large language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Automatic chain of thought prompting in large language models,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.805594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 096056bb-7609-46d7-9374-bfc106197bea · outbound

This paper cites Explain yourself! leveraging language models for commonsense reasoning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Explain yourself! leveraging language models for commonsense reasoning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.797205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d4f42203-1316-4808-9d51-e0046974bcac · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision?.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning What uncertainties do we need in bayesian deep learning for computer vision?

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.788389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 56f7c228-91cf-4c5a-b3eb-6b6833958609 · outbound

This paper cites Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.780145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ab1b873b-b7d7-4853-b588-5e6e947e5c4f · outbound

This paper cites Auxiliary tasks in multi-task learning,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Auxiliary tasks in multi-task learning,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T17:25:50.695216Z

Source-reported events for the cited work

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Observation 6574c7ad-321f-4ab0-be61-916677fd8dd0 · outbound

This paper cites Semeval-2014 task 4: Aspect based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Semeval-2014 task 4: Aspect based sentiment analysis,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.766484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 97c02f6d-e858-4a7d-a3fa-c78d3bd6a295 · outbound

This paper cites Adapt or get left behind: Domain adaptation through bert language model finetuning for aspect- target sentiment classification,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Adapt or get left behind: Domain adaptation through bert language model finetuning for aspect- target sentiment classification,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.758152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 68da2b9e-de0d-482d-a229-4a28a6b7b252 · outbound

This paper cites Instructabsa: Instruction learning for aspect based sentiment analysis,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Instructabsa: Instruction learning for aspect based sentiment analysis,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.749065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2177a847-a59d-47d9-9764-4319a6705c95 · outbound

This paper cites Scaling instruction-finetuned language models,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Scaling instruction-finetuned language models,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.740344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b5cf192-13bc-4cf2-aa2d-f075889d1427 · outbound

This paper cites Think twice before trusting: Self-detection for large language models through comprehensive answer reflection,.

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning Think twice before trusting: Self-detection for large language models through comprehensive answer reflection,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:25:50.731954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation f1b100b5-75c3-4d63-89ee-b4a63864b153 · inbound

Efficiently Integrate Large Language Models with Visual Perception: A Survey from the Training Paradigm Perspective cites this paper.

Efficiently Integrate Large Language Models with Visual Perception: A Survey from the Training Paradigm Perspective Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-08-09T15:04:40.419710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.