2.9k citations · 3.1k across the 14 of their papers we have counts for
15 papers
Seeing Depth but Choosing Cues in Vision-Language Models
Zhengtao Zou, Pekka Marttinen
Do vision-language models use depth information to judge which object is closer, or rely on image-plane cues? We investigate this question through controlled depth--cue conflicts,…
Evidence-State Rewards for Long-Context Reasoning
Ya Gao, Pekka Marttinen
Long-context reasoning requires models to locate, revise, and synthesize evidence distributed across lengthy inputs. Existing long-context RL methods usually reward final answers o…
CBR-to-SQL: Rethinking Retrieval-based Text-to-SQL using Case-based Reasoning in the Healthcare Domain
Hung Nguyen, Hans Moen, Pekka Marttinen
Extracting insights from Electronic Health Record (EHR) databases often requires SQL expertise, creating a barrier for clinical decision-making and research. A promising approach i…
Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models
Zhengtao Zou, Ya Gao, Jiarui Guan +2
Large Vision-Language Models (LVLMs) typically process visual inputs as a prefix to the language decoder. As the model autoregressively generates text, this initial visual informat…
Query-Guided Self-Supervised Summarization of Nursing Notes
Ya Gao, Hans Moen, Saila Koivusalo +2
Nursing notes, an important part of Electronic Health Records (EHRs), track a patient's health during a care episode. Summarizing key information in nursing notes can help clinicia…
Content Reduction, Surprisal and Information Density Estimation for Long Documents
Shaoxiong Ji, Wei Sun, Pekka Marttinen
Many computational linguistic methods have been proposed to study the information content of languages. We consider two interesting research questions: 1) how is information distri…
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection
Shaoxiong Ji, Ya Gao, Pekka Marttinen
Adverse drug events (ADEs) are an important aspect of drug safety. Various texts such as biomedical literature, drug reviews, and user posts on social media and medical forums cont…
A Unified Review of Deep Learning for Automated Medical Coding
Shaoxiong Ji, Wei Sun, Xiaobo Li +6
Automated medical coding, an essential task for healthcare operation and delivery, makes unstructured data manageable by predicting medical codes from clinical documents. Recent ad…
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning
Shaoxiong Ji, Pekka Marttinen
Multitask deep learning has been applied to patient outcome prediction from text, taking clinical notes as input and training deep neural networks with a joint loss function of mul…
Multitask Balanced and Recalibrated Network for Medical Code Prediction
Wei Sun, Shaoxiong Ji, Erik Cambria +1
Human coders assign standardized medical codes to clinical documents generated during patients' hospitalization, which is error-prone and labor-intensive. Automated medical coding…
Multitask Recalibrated Aggregation Network for Medical Code Prediction
Wei Sun, Shaoxiong Ji, Erik Cambria +1
Medical coding translates professionally written medical reports into standardized codes, which is an essential part of medical information systems and health insurance reimburseme…
Does the Magic of BERT Apply to Medical Code Assignment? A Quantitative Study
Shaoxiong Ji, Matti Hölttä, Pekka Marttinen
Unsupervised pretraining is an integral part of many natural language processing systems, and transfer learning with language models has achieved remarkable results in many downstr…
Medical Code Assignment with Gated Convolution and Note-Code Interaction
Shaoxiong Ji, Shirui Pan, Pekka Marttinen
Medical code assignment from clinical text is a fundamental task in clinical information system management. As medical notes are typically lengthy and the medical coding system's c…
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text
Shaoxiong Ji, Erik Cambria, Pekka Marttinen
Medical code assignment, which predicts medical codes from clinical texts, is a fundamental task of intelligent medical information systems. The emergence of deep models in natural…
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Shaoxiong Ji, Shirui Pan, Erik Cambria +2
Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities have become an increasingly popular research dir…