Papers Implicit Relations
“Implicit Relations” 태그가 달린 논문 71편 · 필터 해제
Can AI Agents Detect and Repair Artifact Drift in Network Experiments?
In recent years, AI agents have evolved into capable assistants that carry out multi-step tasks in digital environments. The network systems community is beginning to explore these capabilities in operational and experim…
Implicit RelationsQUIETT: Query-Independent Table Transformation for Robust Reasoning
Real-world tables often contain schema inconsistencies, heterogeneous value formats, and implicit relational structures that degrade table reasoning and question answering. Existing approaches address these issues at que…
Implicit RelationsQuestion AnsweringEcphoryRAG: Re-Imagining Knowledge-Graph RAG via Human Associative Memory
Cognitive neuroscience research indicates that humans leverage cues to activate entity-centered memory traces (engrams) for complex, multi-hop recollection. Inspired by this mechanism, we introduce EcphoryRAG, an entity-…
Implicit RelationsQuestion AnsweringSymMatika: Structure-Aware Symbolic Discovery
Symbolic regression (SR) seeks to recover closed-form mathematical expressions that describe observed data. While existing methods have advanced the discovery of either explicit mappings (i.e., $y = f(\mathbf{x})$) or di…
Implicit RelationsKG-QAGen: A Knowledge-Graph-Based Framework for Systematic Question Generation and Long-Context LLM Evaluation
The increasing context length of modern language models has created a need for evaluating their ability to retrieve and process information across extensive documents. While existing benchmarks test long-context capabili…
Answer GenerationImplicit RelationsQuestion-Answer-GenerationQuestion Generation+1CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors
Channel knowledge map (CKM) is a promising technology to enable environment-aware wireless communications and sensing with greatly enhanced performance, by offering location-specific channel prior information for future …
Data AugmentationDenoisingImplicit RelationsSuper-ResolutionGoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction
Exploring the functions of genes and gene products is crucial to a wide range of fields, including medical research, evolutionary biology, and environmental science. However, discovering new functions largely relies on e…
Implicit RelationsMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONPrediction+1Hypergraph-based Motion Generation with Multi-modal Interaction Relational Reasoning
The intricate nature of real-world driving environments, characterized by dynamic and diverse interactions among multiple vehicles and their possible future states, presents considerable challenges in accurately predicti…
Autonomous VehiclesImplicit RelationsMotion Generationmotion prediction+1Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference
The visual question generation (VQG) task aims to generate human-like questions from an image and potentially other side information (e.g. answer type). Previous works on VQG fall in two aspects: i) They suffer from one …
Graph-to-SequenceImplicit RelationsQuestion GenerationQuestion-GenerationRelation Extraction with Fine-Tuned Large Language Models in Retrieval Augmented Generation Frameworks
Information Extraction (IE) is crucial for converting unstructured data into structured formats like Knowledge Graphs (KGs). A key task within IE is Relation Extraction (RE), which identifies relationships between entiti…
Domain AdaptationImplicit RelationsKnowledge GraphsRAG+5Semantic-Enhanced Relational Metric Learning for Recommender Systems
Recently, relational metric learning methods have been received great attention in recommendation community, which is inspired by the translation mechanism in knowledge graph. Different from the knowledge graph where the…
Implicit RelationsMetric LearningRecommendation SystemsMagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
Image retrieval, i.e., finding desired images given a reference image, inherently encompasses rich, multi-faceted search intents that are difficult to capture solely using image-based measures. Recent works leverage text…
Image RetrievalImplicit RelationsRetrievalSupervised Image Retrieval+2How to Understand "Support"? An Implicit-enhanced Causal Inference Approach for Weakly-supervised Phrase Grounding
Weakly-supervised Phrase Grounding (WPG) is an emerging task of inferring the fine-grained phrase-region matching, while merely leveraging the coarse-grained sentence-image pairs for training. However, existing studies o…
Causal InferencecounterfactualImplicit RelationsPhrase Grounding+1Modeling Balanced Explicit and Implicit Relations with Contrastive Learning for Knowledge Concept Recommendation in MOOCs
The knowledge concept recommendation in Massive Open Online Courses (MOOCs) is a significant issue that has garnered widespread attention. Existing methods primarily rely on the explicit relations between users and knowl…
Contrastive LearningGraph Neural NetworkImplicit RelationsTowards Complementary Knowledge Distillation for Efficient Dense Image Prediction
It has been revealed that small efficient dense image prediction (EDIP) models, trained using the knowledge distillation (KD) framework, encounter two key challenges, including maintaining boundary region completeness an…
Implicit RelationsInstance SegmentationKnowledge DistillationObject+5Unlock Reliable Skill Inference for Quadruped Adaptive Behavior by Skill Graph
Developing robotic intelligent systems that can adapt quickly to unseen wild situations is one of the critical challenges in pursuing autonomous robotics. Although some impressive progress has been made in walking stabil…
Implicit RelationsDual Relation Alignment for Composed Image Retrieval
Composed image retrieval, a task involving the search for a target image using a reference image and a complementary text as the query, has witnessed significant advancements owing to the progress made in cross-modal mod…
Image RetrievalImage-text RetrievalImplicit RelationsRelation+2A Generalized Deep Markov Random Fields Framework for Fake News Detection.
Recently, the wanton dissemination of fake news on social media has adversely affected our lives, rendering automatic fake news detection a pressing issue. Current methods are often fully supervised and typically employ …
ArticlesFake News DetectionImplicit RelationsAnchor Prediction: Automatic Refinement of Internet Links
Internet links enable users to deepen their understanding of a topic by providing convenient access to related information. However, the majority of links are unanchored -- they link to a target webpage as a whole, and r…
Implicit RelationsPredictionK-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imaging
In this paper, we consider the problem of disease diagnosis. Unlike the conventional learning paradigm that treats labels independently, we propose a knowledge-enhanced framework, that enables training visual representat…
AnatomyContrastive LearningImplicit RelationsZero-Shot Learning