Papers Structured Prediction
“Structured Prediction” 태그가 달린 논문 687편 · 필터 해제
Contextual Plackett-Luce: An Efficient Neural Model for Probabilistic Sequence Selection under Ambiguity
Selecting a coherent sequence or subset of elements is a fundamental problem in structured prediction, arising in tasks such as detection, trajectory forecasting, and representative subset selection. In many such setting…
Trajectory ForecastingStructured PredictionA Multi-Head Attention Approach for SLA Compliance Monitoring in Data Centers
Service level agreements (SLAs) in data center colocation contracts define precise thresholds for power, temperature, and humidity, with tiered violation penalties expressed as credits against monthly recurring charges. …
Structured PredictionUltrasound Vision-Language Alignment via Contrastive Learning
Ultrasound foundation models have achieved strong performance on structured prediction tasks but remain exclusively vision-based, limiting zero-shot and few-shot transfer to novel tasks where task-specific annotation is …
Structured PredictionContrastive LearningDomain AdaptationLinear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction
The choice of loss function in classification involves a fundamental trade-off: smooth losses (like Cross-Entropy) enable fast optimization rates but yield slow square-root consistency bounds, while piecewise-linear loss…
Structured PredictionESIA: An Energy-Based Spatiotemporal Interaction-Aware Framework for Pedestrian Intention Prediction
Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and actions by modeling temporal dynamics, social interactions, and environm…
Structured PredictionAutonomous DrivingSTaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction
Structured prediction with large language models requires outputs that are label-accurate, ontology-constrained, structurally valid, and evidence-grounded under label imbalance and heterogeneous group difficulty. We pres…
Structured PredictionPrompt EngineeringEvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs
Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly successful, this paradigm is too narrow for many structured predict…
Structured PredictionArabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models
Large language models (LLMs) perform strongly on many NLP tasks, but their ability to produce explicit linguistic structure remains unclear. We evaluate instruction-tuned LLMs on two structured prediction tasks for Stand…
Structured PredictionDependency ParsingVIVID-Med: LLM-Supervised Structured Pretraining for Deployable Medical ViTs
Vision-language pretraining has driven significant progress in medical image analysis. However, current methods typically supervise visual encoders using one-hot labels or free-form text, neither of which effectively cap…
Lung Nodule ClassificationStructured PredictionECHO: Event-Centric Hypergraph Operations via Multi-Agent Collaboration for Multimedia Event Extraction
Multimedia event extraction (M2E2) aims to predict triggers, ground arguments across text and images, and then assemble them into schema-consistent event records. Recent LLM-based approaches have shown strong potential f…
Structured PredictionEvent ExtractionTimeSpot: Benchmarking Geo-Temporal Understanding in Vision-Language Models in Real-World Settings
Geo-temporal understanding, the ability to infer location, time, and contextual properties from visual input alone, underpins applications such as disaster management, traffic planning, embodied navigation, world modelin…
Structured PredictionHybrid Neural-LLM Pipeline for Morphological Glossing in Endangered Language Documentation: A Case Study of Jungar Tuvan
Interlinear glossed text (IGT) creation remains a major bottleneck in linguistic documentation and fieldwork, particularly for low-resource morphologically rich languages. We present a hybrid automatic glossing pipeline …
Structured PredictionSynthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code
Multimodal geometry reasoning requires models to jointly understand visual diagrams and perform structured symbolic inference, yet current vision--language models struggle with complex geometric constructions due to limi…
Structured Prediction$(α,β)$-Stability for Boosting Vector-Valued Prediction
Despite the widespread use of boosting in structured prediction, a general theoretical understanding of aggregation beyond scalar prediction remains incomplete. We study vector-valued prediction under a target divergence…
Structured PredictionDensity EstimationUnderstanding Degradation with Vision Language Model
Understanding visual degradations is a critical yet challenging problem in computer vision. While recent Vision-Language Models (VLMs) excel at qualitative description, they often fall short in understanding the parametr…
Reinforcement LearningStructured PredictionImage RestorationTAB-PO: Preference Optimization with a Token-Level Adaptive Barrier for Token-Critical Structured Generation
Direct Preference Optimization (DPO) is an effective and widely adopted approach for offline alignment but is poorly matched to ontology-driven structured prediction, where preferred and rejected JSON objects often diffe…
Information ExtractionStructured PredictionReliable Use of Lemmas via Eligibility Reasoning and Section$-$Aware Reinforcement Learning
Recent large language models (LLMs) perform strongly on mathematical benchmarks yet often misapply lemmas, importing conclusions without validating assumptions. We formalize lemma$-$judging as a structured prediction tas…
Reinforcement LearningStructured PredictionLearning to Guide Local Search for MPE Inference in Probabilistic Graphical Models
Most Probable Explanation (MPE) inference in Probabilistic Graphical Models (PGMs) is a fundamental yet computationally challenging problem arising in domains such as diagnosis, planning, and structured prediction. In ma…
Structured PredictionContext Structure Reshapes the Representational Geometry of Language Models
Large Language Models (LLMs) have been shown to organize the representations of input sequences into straighter neural trajectories in their deep layers, which has been hypothesized to facilitate next-token prediction vi…
Structured PredictionSynRXN: An Open Benchmark and Curated Dataset for Computational Reaction Modeling
We present SynRXN, a unified benchmarking framework and open-data resource for computer-aided synthesis planning (CASP). SynRXN decomposes end-to-end synthesis planning into five task families, covering reaction rebalanc…
Structured Prediction