Papers Semantic Composition
“Semantic Composition” 태그가 달린 논문 110편 · 필터 해제
The Emergence of Grammar through Reinforcement Learning
The evolution of grammatical systems of syntactic and semantic composition is modeled here with a novel application of reinforcement learning theory. To test the functionalist thesis that speakers' expressive purposes sh…
Learning Theoryreinforcement-learningReinforcement LearningSemantic CompositionIP-Composer: Semantic Composition of Visual Concepts
Content creators often draw inspiration from multiple visual sources, combining distinct elements to craft new compositions. Modern computational approaches now aim to emulate this fundamental creative process. Although …
Image GenerationSemantic CompositionEnergyMoGen: Compositional Human Motion Generation with Energy-Based Diffusion Model in Latent Space
Diffusion models, particularly latent diffusion models, have demonstrated remarkable success in text-driven human motion generation. However, it remains challenging for latent diffusion models to effectively compose mult…
Motion GenerationSemantic CompositionDiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in phot…
AttributeSemantic CompositionDistributed Intelligent Integrated Sensing and Communications: The 6G-DISAC Approach
This paper introduces the concept of Distributed Intelligent integrated Sensing and Communications (DISAC), which expands the capabilities of Integrated Sensing and Communications (ISAC) towards distributed architectures…
ISACManagementSemantic CompositionSynthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
We introduce a synthetic dataset called Sentences Involving Complex Compositional Knowledge (SICCK) and a novel analysis that investigates the performance of Natural Language Inference (NLI) models to understand composit…
Natural Language InferenceNegationSemantic CompositionSentenceSemantic Composition in Visually Grounded Language Models
What is sentence meaning and its ideal representation? Much of the expressive power of human language derives from semantic composition, the mind's ability to represent meaning hierarchically & relationally over constitu…
Image CaptioningInductive BiasPhilosophyQuestion Answering+6Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings
Past work probing compositionality in sentence embedding models faces issues determining the causal impact of implicit syntax representations. Given a sentence, we construct a neural module net based on its syntax parse …
Semantic CompositionSentenceSentence EmbeddingSentence-Embedding+1Categorizing Semantic Representations for Neural Machine Translation
Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks. However, they have recently been shown to suffer limitation in compositional generalization, failing to effecti…
Machine TranslationNMTSemantic CompositionTranslationBOSS: Bottom-up Cross-modal Semantic Composition with Hybrid Counterfactual Training for Robust Content-based Image Retrieval
Content-Based Image Retrieval (CIR) aims to search for a target image by concurrently comprehending the composition of an example image and a complementary text, which potentially impacts a wide variety of real-world app…
Content-Based Image RetrievalcounterfactualImage RetrievalRetrieval+1Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering
A key challenge in video question answering is how to realize the cross-modal semantic alignment between textual concepts and corresponding visual objects. Existing methods mostly seek to align the word representations w…
Question AnsweringSemantic CompositionVideo Question AnsweringSemantic Composition with PSHRG for Derivation Tree Reconstruction from Graph-Based Meaning Representations
We introduce a data-driven approach to generating derivation trees from meaning representation graphs with probabilistic synchronous hyperedge replacement grammar (PSHRG). SHRG has been used to produce meaning representa…
Semantic CompositionDesign considerations for a hierarchical semantic compositional framework for medical natural language understanding
Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods.…
Natural Language UnderstandingSemantic CompositionSentenceMixSyn: Learning Composition and Style for Multi-Source Image Synthesis
Synthetic images created by generative models increase in quality and expressiveness as newer models utilize larger datasets and novel architectures. Although this photorealism is a positive side-effect from a creative s…
DiversityImage GenerationSemantic CompositionA Well-Composed Text is Half Done! Semantic Composition Sampling for Diverse Conditional Generation
We propose Composition Sampling, a simple but effective method to generate higher quality diverse outputs for conditional generation tasks, compared to previous stochastic decoding strategies. It builds on recently propo…
Question GenerationQuestion-GenerationSemantic CompositionSemantic Prediction: Which One Should Come First, Recognition or Prediction?
The ultimate goal of video prediction is not forecasting future pixel-values given some previous frames. Rather, the end goal of video prediction is to discover valuable internal representations from the vast amount of a…
Decision MakingPredictionSemantic CompositionVideo PredictionImage Synthesis via Semantic Composition
In this paper, we present a novel approach to synthesize realistic images based on their semantic layouts. It hypothesizes that for objects with similar appearance, they share similar representation. Our method establish…
Image GenerationSemantic CompositionA Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking
To inhibit the spread of rumorous information and its severe consequences, traditional fact checking aims at retrieving relevant evidence to verify the veracity of a given claim. Fact checking methods typically use knowl…
Fact CheckingKnowledge GraphsSemantic CompositionQuantum Mathematics in Artificial Intelligence
In the decade since 2010, successes in artificial intelligence have been at the forefront of computer science and technology, and vector space models have solidified a position at the forefront of artificial intelligence…
Information RetrievalNegationPositionRetrieval+1SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
Data mixing augmentation has proved effective in training deep models. Recent methods mix labels mainly based on the mixture proportion of image pixels. As the main discriminative information of a fine-grained image usua…
Fine-Grained Image ClassificationSemantic CompositionSemantic correspondence