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Referring expression generation

Generate referring expressions

Papers

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Showing 26–50 of 84 papers

TitleStatusHype
Non-neural Models Matter: A Re-evaluation of Neural Referring Expression Generation Systems—0
Using Referring Expression Generation to Model Literary Style—0
Decoupling Pragmatics: Discriminative Decoding for Referring Expression Generation—0
What can Neural Referential Form Selectors Learn?—0
Enriching the E2E datasetCode0
Perspective-corrected Spatial Referring Expression Generation for Human-Robot Interaction—0
Visual Question Answering based on Local-Scene-Aware Referring Expression Generation—0
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training—0
Generating Quantified Referring Expressions through Attention-Driven Incremental Perception—0
OMEGA : A probabilistic approach to referring expression generation in a virtual environment—0
CoNAN: A Complementary Neighboring-based Attention Network for Referring Expression Generation—0
Referring to what you know and do not know: Making Referring Expression Generation Models Generalize To Unseen Entities—0
Lessons from Computational Modelling of Reference Production in Mandarin and English—0
Fuzzy Logic for Vagueness Management in Referring Expression Generation—0
Toward Forgetting-Sensitive Referring Expression Generationfor Integrated Robot Architectures—0
Informativity in Image Captions vs. Referring Expressions—0
MuDoCo: Corpus for Multidomain Coreference Resolution and Referring Expression Generation—0
A case study on context-bound referring expression generation—0
Improving Quality and Efficiency in Plan-based Neural Data-to-Text GenerationCode0
Referring Expression Generation Using Entity ProfilesCode0
Augmenting Robot Knowledge Consultants with Distributed Short Term Memory—0
Adapting Descriptions of People to the Point of View of a Moving Observer—0
Enriching the WebNLG corpusCode0
Decoding Strategies for Neural Referring Expression Generation—0
Statistical NLG for Generating the Content and Form of Referring Expressions—0
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All datasetsColonINST-v1 (Seen)ColonINST-v1 (Unseen)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ColonGPT (w/ LoRA, w/o extra data)Accuray99.96—Unverified
2LLaVA-v1.5 (w/ LoRA, w/ extra data)Accuray99.32—Unverified
3LLaVA-Med-v1.5 (w/ LoRA, w/o extra data)Accuray99.3—Unverified
4MGM-2B (w/o LoRA, w/ extra data)Accuray98.75—Unverified
5LLaVA-v1.5 (w/ LoRA, w/o extra data)Accuray98.58—Unverified
6MGM-2B (w/o LoRA, w/o extra data)Accuray98.17—Unverified
7MobileVLM-1.7B (w/ LoRA, w/ extra data)Accuray97.87—Unverified
8MobileVLM-1.7B (w/o LoRA, w/ extra data)Accuray97.78—Unverified
9LLaVA-Med-v1.0 (w/o LoRA, w/o extra data)Accuray97.74—Unverified
10LLaVA-Med-v1.0 (w/o LoRA, w/ extra data)Accuray97.35—Unverified
#ModelMetricClaimedVerifiedStatus
1LLaVA-Med-v1.5 (w/ LoRA, w/ extra data)Accuray70—Unverified
2LLaVA-v1 (w/ LoRA, w/ extra data)Accuray46.85—Unverified