Prayag Tiwari

Associate Professor@Halmstad University·瑞典·OpenReview

研究方向

LLMs · Multimodal Learning · AI in Drug Discovery · Unsupervised Feature Selection Method · Quantum Kernel Methods · Quantum Machine Learning · Machine Learning

Prayag Tiwari

NurValues: Real-World Nursing Values Evaluation for Large Language Models in Clinical Context

Efficient Multimodal Spatial Reasoning via Dynamic and Asymmetric Routing

Graph Logic Flows: Geometry-Driven, Certificate-Carrying Reasoning on Dynamic Graphs

Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models

CP Merging: Joint LoRA Merging using Canonical Polyadic Decomposition

Multi-Linear Subspace Distance: A New Criterion for Tensor Feature Selection

Benchmarking LLMs on Authentic Cases from Medical Journals

Efficient Similarity-Based Fast Unlearning via Pearson Correlation Detection

IntelliAsk: Learning to Ask Critical Questions with Human-Aligned Rewards

Latent-to-Observable Score Correction for Probabilistic Time Series Imputation

Unlocking Clinical Potential: Beyond Single-to-Tri-Phase CT with Dynamic Fusion for Precision Liver Tumor Segmentation

Reasoning Beyond Points: A Visual Introspective Approach for Few-Shot 3D Segmentation

DyPolySeg: Taylor Series-Inspired Dynamic Polynomial Fitting Network for Few-shot Point Cloud Semantic Segmentation

Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance

Dynamic Taylor Convolutional Neural Network for Few-Shot Point Cloud Semantic Segmentation

Interpretable and Adaptive Graph Contrastive Learning with Information Sharing for Biomedical Link Prediction