L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training | Paper Citation Record

Observation af9e9b67-ed51-43f0-a289-8f9970342520 · outbound

This paper cites Learning cnn-lstm architectures for image caption generation,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Learning cnn-lstm architectures for image caption generation,

Reference 1

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Observation 98920df9-8da1-4c92-b48d-4e976d93e013 · outbound

This paper cites Image captioning through image transformer,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Image captioning through image transformer,

Reference 2

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Observation 2b78848c-363e-4dbb-818d-7779191acc0b · outbound

This paper cites Meshed-memory transformer for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Meshed-memory transformer for image captioning,

Reference 3

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Observation 724a695d-4006-446b-b5d5-c6b7680e669c · outbound

This paper cites Bottom-up and top-down attention for image captioning and visual question answering,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Bottom-up and top-down attention for image captioning and visual question answering,

Reference 4

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Observation 3a749b07-904b-437b-a0b3-6be7fa4d1177 · outbound

This paper cites Self- critical sequence training for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Self- critical sequence training for image captioning,

Reference 5

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Observation 21ca654c-8798-4748-ae07-cac4c4654afa · outbound

This paper cites Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image cap- tioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image cap- tioning,

Reference 6

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Observation 6233736e-00d0-45bb-a043-a7cba9c56470 · outbound

This paper cites Microsoft coco: Common objects in context,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Microsoft coco: Common objects in context,

Reference 7

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Observation 8fe3c809-e63e-4f17-ae2a-7ed19de952a0 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Bleu: a method for automatic evaluation of machine translation,

Reference 8

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Observation c7189918-21d6-4020-a0d7-b828d7412d6d · outbound

This paper cites Cider: Consensus- based image description evaluation,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Cider: Consensus- based image description evaluation,

Reference 9

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This paper cites Bertscore: Evaluating text generation with bert,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Bertscore: Evaluating text generation with bert,

Reference 10

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Observation 196d3fa2-6bb0-4897-a325-0db460aa2a3f · outbound

This paper cites What you see is what you read? improv- ing text-image alignment evaluation,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training What you see is what you read? improv- ing text-image alignment evaluation,

Reference 11

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Observation 738d87d5-2d8d-40ca-a429-d349426f4e66 · outbound

This paper cites Fast, accurate, and lightweight memory-enhanced embedding learning framework for image-text retrieval,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Fast, accurate, and lightweight memory-enhanced embedding learning framework for image-text retrieval,

Reference 12

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Observation 34fd9183-3893-4f64-bb97-884567a1abe8 · outbound

This paper cites Vilbertscore: Evaluating image caption using vision-and-language bert,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Vilbertscore: Evaluating image caption using vision-and-language bert,

Reference 13

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This paper cites Image-text alignment and retrieval using light-weight transformer,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Image-text alignment and retrieval using light-weight transformer,

Reference 14

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This paper cites UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning

Reference 15

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Observation b11e06f7-676b-404a-b3d5-0d11a036e1a1 · outbound

This paper cites Less is more: Clipbert for video-and-language learning via sparse sampling,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Less is more: Clipbert for video-and-language learning via sparse sampling,

Reference 16

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Observation 523b857d-58f0-4d9e-94a8-81e3b919172a · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,

Reference 17

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Observation 10672b9f-a868-466f-8a6c-b1c479216c38 · outbound

This paper cites Quality estimation for image captions based on large-scale human evaluations,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Quality estimation for image captions based on large-scale human evaluations,

Reference 18

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Observation 067683fa-cef1-4c83-811c-27ee9be55865 · outbound

This paper cites Revealing the dark secrets of bert,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Revealing the dark secrets of bert,

Reference 19

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Observation 104ac830-39ae-4fed-9f7f-ce993210402d · outbound

This paper cites Minivit: Compressing vision transformers with weight multiplexing,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Minivit: Compressing vision transformers with weight multiplexing,

Reference 20

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Observation 8ad54b67-70ec-4ebe-9c0d-6cd9ca908c74 · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 21

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Observation ee9aa492-63a3-4d64-b84b-55e70a95c154 · outbound

This paper cites Enabling multimodal generation on clip via vision-language knowledge distilla- tion,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Enabling multimodal generation on clip via vision-language knowledge distilla- tion,

Reference 22

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Observation 65ec115c-e93a-478d-a9bb-c43a8a8ca597 · outbound

This paper cites CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks

Reference 23

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Observation 60ba08d4-fc9b-4506-a040-d906a169dae3 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Learning transferable visual models from natural language supervision,

Reference 24

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Observation c0f769db-72fa-4407-b8cd-bcbe1e6ffbd3 · outbound

This paper cites Sca-cnn: Spatial and channel-wise attention in convolutional networks for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Sca-cnn: Spatial and channel-wise attention in convolutional networks for image captioning,

Reference 25

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Observation 571e6b59-0e11-4213-bfca-acffcc3b3899 · outbound

This paper cites Knowing when to look: Adaptive attention via a visual sentinel for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Knowing when to look: Adaptive attention via a visual sentinel for image captioning,

Reference 26

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Observation c435e904-4efc-468e-90e1-77a151c923e6 · outbound

This paper cites Know more say less: Image captioning based on scene graphs,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Know more say less: Image captioning based on scene graphs,

Reference 27

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Observation 9192a4e7-23b4-4c75-aad3-0e2a41fc051a · outbound

This paper cites High-quality image cap- tioning with fine-grained and semantic-guided visual attention,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training High-quality image cap- tioning with fine-grained and semantic-guided visual attention,

Reference 28

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This paper cites Multimodal transformer with multi- view visual representation for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Multimodal transformer with multi- view visual representation for image captioning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:18:56.954306Z

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This paper cites Compact bidirectional transformer for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Compact bidirectional transformer for image captioning,

Reference 30

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This paper cites Task-adaptive attention for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Task-adaptive attention for image captioning,

Reference 31

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This paper cites Textual context-aware dense captioning with diverse words,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Textual context-aware dense captioning with diverse words,

Reference 32

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This paper cites Meteor: An automatic metric for mt evalua- tion with improved correlation with human judgments,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Meteor: An automatic metric for mt evalua- tion with improved correlation with human judgments,

Reference 33

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This paper cites Rouge: A package for automatic evaluation of summaries,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Rouge: A package for automatic evaluation of summaries,

Reference 34

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This paper cites Spice: Semantic propositional image caption evaluation,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Spice: Semantic propositional image caption evaluation,

Reference 35

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 36

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This paper cites Clipscore: A reference-free evaluation metric for image captioning,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Clipscore: A reference-free evaluation metric for image captioning,

Reference 37

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This paper cites Tiger: Text-to-image grounding for image caption evalua- tion,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Tiger: Text-to-image grounding for image caption evalua- tion,

Reference 38

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This paper cites Em- score: Evaluating video captioning via coarse-grained and fine-grained embedding matching,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Em- score: Evaluating video captioning via coarse-grained and fine-grained embedding matching,

Reference 39

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This paper cites Gpt-3: Its nature, scope, limits, and consequences,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Gpt-3: Its nature, scope, limits, and consequences,

Reference 40

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This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehen- sion,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehen- sion,

Reference 41

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This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 42

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This paper cites Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks

Reference 44

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This paper cites VL-BERT: Pre-training of Generic Visual-Linguistic Representations.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training VL-BERT: Pre-training of Generic Visual-Linguistic Representations

Reference 45

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This paper cites Slip: Self-supervision meets language-image pre-training,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Slip: Self-supervision meets language-image pre-training,

Reference 46

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This paper cites Pruning Filters for Efficient ConvNets.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Pruning Filters for Efficient ConvNets

Reference 47

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This paper cites Vision Transformer Pruning.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Vision Transformer Pruning

Reference 48

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This paper cites Post-training quantization for vision transformer,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Post-training quantization for vision transformer,

Reference 49

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Observation 0505ab65-2ef6-496c-98ae-c4ec38866818 · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Tinyvit: Fast pretraining distillation for small vision transformers,

Reference 50

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Observation 0b0011c6-d04c-4753-abb2-3a5bdf78d27f · outbound

This paper cites Tinybert: Distilling bert for natural language understanding,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Tinybert: Distilling bert for natural language understanding,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:18:54.259692Z

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Observation 2b89c3d1-403f-4093-b9d5-8456c1de0eb0 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 52

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This paper cites Training data-efficient image transformers & distillation through attention,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Training data-efficient image transformers & distillation through attention,

Reference 53

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This paper cites Attention is all you need,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Attention is all you need,

Reference 54

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 55

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Bag of tricks for image classification with convolutional neural networks,

Reference 56

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Making convolutional networks shift-invariant again,

Reference 57

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Discriminability objective for training descriptive captions,

Reference 58

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training ImageNet Large Scale Visual Recognition Challenge,

Reference 59

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This paper cites Framing image description as a ranking task: Data, models and evaluation metrics,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Framing image description as a ranking task: Data, models and evaluation metrics,

Reference 60

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training From Images to Sentences through Scene Description Graphs using Commonsense Reasoning and Knowledge

Reference 61

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Consensus-based image description evaluation,

Reference 62

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This paper cites Foil it! find one mismatch between image and language caption,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Foil it! find one mismatch between image and language caption,

Reference 63

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This paper cites Deep visual-semantic alignments for gen- erating image descriptions,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Deep visual-semantic alignments for gen- erating image descriptions,

Reference 64

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Vinvl: Revisiting visual representations in vision-language models,

Reference 65

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This paper cites Adam: A method for stochastic optimization,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Adam: A method for stochastic optimization,

Reference 66

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This paper cites Improving image captioning evaluation by considering inter references variance,.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Improving image captioning evaluation by considering inter references variance,

Reference 67

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This paper cites Concrete Problems in AI Safety.

L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Concrete Problems in AI Safety

Reference 68

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L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training Spontaneous Reward Hacking in Iterative Self-Refinement

Reference 69

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