Paper Citation Record · LEDGER

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.09139.

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

pith.paper-citation-record.v1
2505.09139 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:42:41.687023Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

32 of 32 outbound references displayed

verified exact1
verified fuzzy20
unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7603201b-6dcb-498c-a005-1043a692404a · outbound

This paper cites Learning to prompt for vision- language models,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Learning to prompt for vision- language models,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T21:42:41.572893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75ec0ca4-74e9-448a-a90e-f5c49e317127 · outbound

This paper cites Sugarcrepe++ dataset: Vision-language model sensitivity to semantic and lexical alterations,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Sugarcrepe++ dataset: Vision-language model sensitivity to semantic and lexical alterations,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:42.041256Z

Source-reported events for the cited work

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Observation d256b88a-8032-4862-853d-846f44c8634b · outbound

This paper cites Language- driven active learning for diverse open-set 3d object detection,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Language- driven active learning for diverse open-set 3d object detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:42.030510Z

Source-reported events for the cited work

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Observation 26550ea8-a1ad-445f-96ce-d728351dfbf3 · outbound

This paper cites Evaluating multimodal vision- language model prompting strategies for visual question answering in road scene understanding,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Evaluating multimodal vision- language model prompting strategies for visual question answering in road scene understanding,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:42.018973Z

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Observation f5a869cc-dda4-466b-b7aa-c4c867924982 · outbound

This paper cites Ipo: Interpretable prompt optimization for vision-language models,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Ipo: Interpretable prompt optimization for vision-language models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:42.007172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3ba5883b-648a-4ed1-829b-2acbf046928d · outbound

This paper cites African or European Swallow? Benchmarking Large Vision-Language Models for Fine-Grained Object Classification.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models African or European Swallow? Benchmarking Large Vision-Language Models for Fine-Grained Object Classification

Reference 6

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Source-reported events for the cited work

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Observation 9ec0c7fa-59b7-4954-ad58-62752c0cfd0f · outbound

This paper cites Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T21:42:41.594933Z

Source-reported events for the cited work

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Observation 8f3f4180-d557-4cc0-9e10-f145d97e4f83 · outbound

This paper cites Litai: Enhanc- ing multimodal literature understanding and mining with generative ai,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Litai: Enhanc- ing multimodal literature understanding and mining with generative ai,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.995160Z

Source-reported events for the cited work

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Observation c85506d2-1af8-4bef-bcc2-9fc3ee759f99 · outbound

This paper cites Gaugetracker: Ai- powered cost-effective analog gauge monitoring system,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Gaugetracker: Ai- powered cost-effective analog gauge monitoring system,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.984307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b36ad1f3-5eea-4d71-b974-add9164df451 · outbound

This paper cites Reframing: Detector-specific prompt tuning for enhancing open-vocabulary object detection,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Reframing: Detector-specific prompt tuning for enhancing open-vocabulary object detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.971796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1cc6e409-038b-475c-8652-9992f3eea356 · outbound

This paper cites Learning to prompt for open-vocabulary object detection with vision-language model,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Learning to prompt for open-vocabulary object detection with vision-language model,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.961622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7203793-ab5e-4c3e-a475-021eb53b7c98 · outbound

This paper cites T-rex2: Towards generic object detection via text-visual prompt synergy,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models T-rex2: Towards generic object detection via text-visual prompt synergy,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.950009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fbd40de9-9d96-482f-8195-296874da1597 · outbound

This paper cites Fine-grained visual prompting,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Fine-grained visual prompting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.938726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2b90c45a-8fbe-4687-90fc-46188ddab070 · outbound

This paper cites Prompt distribution learning,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Prompt distribution learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.927311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7a43598e-c383-484d-8744-279cd31a5bd1 · outbound

This paper cites CamoSAM2: SAM2-oriented Prompt Auto-Refinement for Video Camouflaged Object Detection.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models CamoSAM2: SAM2-oriented Prompt Auto-Refinement for Video Camouflaged Object Detection

Reference 15

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Source-reported events for the cited work

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Observation 6b2d8bd4-5cdd-48b6-b769-a5aa720bd6ef · outbound

This paper cites Segment anything,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Segment anything,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T21:42:41.624757Z

Source-reported events for the cited work

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Observation beeb63d5-7da6-47d7-a429-cf8ad1fb9caa · outbound

This paper cites Zero-shot nuclei detection via visual-language pre-trained models,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Zero-shot nuclei detection via visual-language pre-trained models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.909683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee667a81-6997-4b54-9b86-cf36c04a0c9d · outbound

This paper cites Attriprompter: Auto-prompting with attribute semantics for zero-shot nuclei detection via visual-language pre-trained models.,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Attriprompter: Auto-prompting with attribute semantics for zero-shot nuclei detection via visual-language pre-trained models.,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.898033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a1f85efc-6c0c-40f7-932b-4b3eed88544a · outbound

This paper cites Self-driving cars dataset.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Self-driving cars dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.887232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2a49d303-1671-44e0-903d-91029f66a08b · outbound

This paper cites GPT-4o System Card.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models GPT-4o System Card

Reference 20

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Source-reported events for the cited work

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Observation 2312ff62-e95c-409a-8b8c-f3dd0afbd53c · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre- trained transformers,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Minilm: Deep self-attention distillation for task-agnostic compression of pre- trained transformers,

Reference 21

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Source-reported events for the cited work

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Observation c0694e4e-bc3e-4a2c-b8c6-cbf330af1f56 · outbound

This paper cites Scaling open-vocabulary object detection,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Scaling open-vocabulary object detection,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.870537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e41b3136-eddb-46a5-9a3f-c2bcded86580 · outbound

This paper cites Crowdtruth measures for language ambiguity,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Crowdtruth measures for language ambiguity,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.859813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8cd4e493-8926-4a22-94da-75d1cf9b541c · outbound

This paper cites Requirements for tools for ambiguity identification and measurement in natural lan- guage requirements specifications,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Requirements for tools for ambiguity identification and measurement in natural lan- guage requirements specifications,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.848694Z

Source-reported events for the cited work

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Observation 6461ef41-3c37-4a3f-ad35-3902f5c59b33 · outbound

This paper cites Ambiguity identification and measurement in natural language texts,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Ambiguity identification and measurement in natural language texts,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.837427Z

Source-reported events for the cited work

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Observation bea0b1a8-3902-47f7-ae95-a52248a7f035 · outbound

This paper cites Generation and comprehension of unambiguous object descriptions,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Generation and comprehension of unambiguous object descriptions,

Reference 26

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Source-reported events for the cited work

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Observation aef0477e-610f-4326-929c-da3b15c8869e · outbound

This paper cites Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T21:42:41.667620Z

Source-reported events for the cited work

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Observation 0ee895a9-a78b-4357-9175-a5057f7e8411 · outbound

This paper cites an unresolved cited work.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:42:41.820024Z

Source-reported events for the cited work

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Observation 1c0b5a4d-c29a-412c-87a6-dc6994cf51c0 · outbound

This paper cites Evaluating Cascaded Methods of Vision-Language Models for Zero-Shot Detection and Association of Hardhats for Increased Construction Safety.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Evaluating Cascaded Methods of Vision-Language Models for Zero-Shot Detection and Association of Hardhats for Increased Construction Safety

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:42:41.734538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6070081-f4a4-4a2b-9927-5c10c50846c7 · outbound

This paper cites Evaluating vision-language models for zero- shot detection, classification, and association of motorcycles, passengers, and helmets,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Evaluating vision-language models for zero- shot detection, classification, and association of motorcycles, passengers, and helmets,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.806986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a94be189-c20e-4da3-b11d-7f05f0df61f4 · outbound

This paper cites Driver activity classification using generalizable representations from vision- language models,.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Driver activity classification using generalizable representations from vision- language models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:42:41.795635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 55e5b0ed-2023-4475-8c7c-239c54ad6b01 · outbound

This paper cites Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety.

Beyond General Prompts: Automated Prompt Refinement using Contrastive Class Alignment Scores for Disambiguating Objects in Vision-Language Models Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T21:42:41.687023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.