I‐Chen Wu
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View article: CourtGuard: A Local, Multiagent Prompt Injection Classifier
CourtGuard: A Local, Multiagent Prompt Injection Classifier Open
As large language models (LLMs) become integrated into various sensitive applications, prompt injection, the use of prompting to induce harmful behaviors from LLMs, poses an ever increasing risk. Prompt injection attacks can cause LLMs to …
View article: Application of BIM Technology to Soil Layer Risk Analysis for Enhanced Accuracy and Informed Decision-Making in Geotechnical Engineering
Application of BIM Technology to Soil Layer Risk Analysis for Enhanced Accuracy and Informed Decision-Making in Geotechnical Engineering Open
View article: A degradation-related slow feature analysis for equipment health indicator extraction and remaining useful life prediction
A degradation-related slow feature analysis for equipment health indicator extraction and remaining useful life prediction Open
View article: Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning
Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning Open
Multi-agent reinforcement Learning (MARL) is often challenged by the sight range dilemma, where agents either receive insufficient or excessive information from their environment. In this paper, we propose a novel method, called Dynamic Si…
View article: Online Learning of Counter Categories and Ratings in PvP Games
Online Learning of Counter Categories and Ratings in PvP Games Open
In competitive games, strength ratings like Elo are widely used to quantify player skill and support matchmaking by accounting for skill disparities better than simple win rate statistics. However, scalar ratings cannot handle complex intr…
View article: Clinical Outcomes of Neoadjuvant Chemoradiation Versus Perioperative Chemotherapy in Patients with Locally Advanced Adenocarcinoma of the Esophagus and Esophagogastric Junction: A Systemic Review and Meta-Analysis
Clinical Outcomes of Neoadjuvant Chemoradiation Versus Perioperative Chemotherapy in Patients with Locally Advanced Adenocarcinoma of the Esophagus and Esophagogastric Junction: A Systemic Review and Meta-Analysis Open
View article: Increased autophagy activity suppresses hyperglycemia-related colorectal cancer tumorigenesis both in vitro and in vivo
Increased autophagy activity suppresses hyperglycemia-related colorectal cancer tumorigenesis both in vitro and in vivo Open
Hyperglycemia contributes to recurrence, poor survival, and drug resistance in colorectal cancer (CRC) patients. Overexpression of G9a (euchromatic histone-lysine N-methyltransferase 2, EHMT2), together with decreased autophagy activity, h…
View article: Access to care improves EHR reliability and clinical risk prediction model performance
Access to care improves EHR reliability and clinical risk prediction model performance Open
Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliability and resulting clinical models are poorly understood. Using an All of Us dataset of 134…
View article: Solving 7x7 Killall-Go with Seki Database
Solving 7x7 Killall-Go with Seki Database Open
Game solving is the process of finding the theoretical outcome for a game, assuming that all player choices are optimal. This paper focuses on a technique that can reduce the heuristic search space significantly for 7x7 Killall-Go. In Go a…
View article: Bridging Local and Global Knowledge via Transformer in Board Games
Bridging Local and Global Knowledge via Transformer in Board Games Open
Although AlphaZero has achieved superhuman performance in board games, recent studies reveal its limitations in handling scenarios requiring a comprehensive understanding of the entire board, such as recognizing long-sequence patterns in G…
View article: Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis Open
How can balance be quantified in game settings? This question is crucial for game designers, especially in player-versus-player (PvP) games, where analyzing the strength relations among predefined team compositions-such as hero combination…
View article: Gradient-based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning
Gradient-based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning Open
Deep Reinforcement Learning (DRL) has achieved remarkable success, ranging from complex computer games to real-world applications, showing the potential for intelligent agents capable of learning in dynamic environments. However, its appli…
View article: Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach
Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach Open
Pommerman is a multi-agent environment that has received considerable attention from researchers in recent years. This environment is an ideal benchmark for multi-agent training, providing a battleground for two teams with communication ca…
View article: Correction: Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire
Correction: Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire Open
[This corrects the article DOI: 10.1371/journal.pone.0258040.].
View article: Special Issue on Advances in Computer Chinese Chess
Special Issue on Advances in Computer Chinese Chess Open
View article: PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping Open
Proximal Policy Optimization algorithm employing a clipped surrogate objective (PPO-Clip) is a prominent exemplar of the policy optimization methods. However, despite its remarkable empirical success, PPO-Clip lacks theoretical substantiat…
View article: Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem
Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem Open
Job-shop scheduling problem (JSP) is a mathematical optimization problem widely used in industries like manufacturing, and flexible JSP (FJSP) is also a common variant. Since they are NP-hard, it is intractable to find the optimal solution…
View article: Lung cancer cells detection by a photoelectrochemical MoS<sub>2</sub> biosensing chip
Lung cancer cells detection by a photoelectrochemical MoS<sub>2</sub> biosensing chip Open
This research aims to explore the potential application of this approach in the production of biosensor chips. The biosensor chip is utilized for the identification and examination of early-stage lung cancer cells. The findings of the opti…
View article: PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping Open
Proximal Policy Optimization algorithm employing a clipped surrogate objective (PPO-Clip) is a prominent exemplar of the policy optimization methods. However, despite its remarkable empirical success, PPO-Clip lacks theoretical substantiat…
View article: Game Solving with Online Fine-Tuning
Game Solving with Online Fine-Tuning Open
Game solving is a similar, yet more difficult task than mastering a game. Solving a game typically means to find the game-theoretic value (outcome given optimal play), and optionally a full strategy to follow in order to achieve that outco…
View article: Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem
Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem Open
Job-shop scheduling problem (JSP) is a mathematical optimization problem widely used in industries like manufacturing, and flexible JSP (FJSP) is also a common variant. Since they are NP-hard, it is intractable to find the optimal solution…
View article: Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games Open
In this paper, we propose a new approach called Adaptive Behavioral Costs in Reinforcement Learning (ABC-RL) for training a human-like agent with competitive strength. While deep reinforcement learning agents have recently achieved superhu…
View article: Image-based Regularization for Action Smoothness in Autonomous Miniature Racing Car with Deep Reinforcement Learning
Image-based Regularization for Action Smoothness in Autonomous Miniature Racing Car with Deep Reinforcement Learning Open
Deep reinforcement learning has achieved significant results in low-level controlling tasks. However, for some applications like autonomous driving and drone flying, it is difficult to control behavior stably since the agent may suddenly c…
View article: Belun Ring (Belun Sleep System BLS-100): Deep learning-facilitated wearable enables obstructive sleep apnea detection, apnea severity categorization, and sleep stage classification in patients suspected of obstructive sleep apnea
Belun Ring (Belun Sleep System BLS-100): Deep learning-facilitated wearable enables obstructive sleep apnea detection, apnea severity categorization, and sleep stage classification in patients suspected of obstructive sleep apnea Open
Belun Ring with second-generation algorithms detected OSA with good accuracy and demonstrated a moderate-to-substantial agreement in categorizing OSA severity and classifying sleep stages.
View article: 0954 CORRELATION OF PULSE RATE VARIABILITY (PRV) AND HEART RATE VARIABILITY (HRV) METRICS DURING SLEEP IN SUBJECTS SUSPECTED OF OSA
0954 CORRELATION OF PULSE RATE VARIABILITY (PRV) AND HEART RATE VARIABILITY (HRV) METRICS DURING SLEEP IN SUBJECTS SUSPECTED OF OSA Open
Introduction Whether photoplethysmography (PPG)-derived pulse rate variability (PRV) metrics can be surrogates for ECG-derived heart rate variability (HRV) is a decade-long debate. Very few studies have assessed the performance of PRV metr…
View article: Reinforcement Learning for Picking Cluttered General Objects with Dense Object Descriptors
Reinforcement Learning for Picking Cluttered General Objects with Dense Object Descriptors Open
Picking cluttered general objects is a challenging task due to the complex geometries and various stacking configurations. Many prior works utilize pose estimation for picking, but pose estimation is difficult on cluttered objects. In this…
View article: Learning Sim-to-Real Dense Object Descriptors for Robotic Manipulation
Learning Sim-to-Real Dense Object Descriptors for Robotic Manipulation Open
It is crucial to address the following issues for ubiquitous robotics manipulation applications: (a) vision-based manipulation tasks require the robot to visually learn and understand the object with rich information like dense object desc…
View article: VeryLongCat won the Mahjong tournament
VeryLongCat won the Mahjong tournament Open
View article: The 2022 Computer Olympiad
The 2022 Computer Olympiad Open
The 25th Computer Olympiad was held online during July/August 2022. With 53 participating programs competing in 18 events, the event was a success.
View article: Analyses of Tabular AlphaZero on Strongly-Solved Stochastic Games
Analyses of Tabular AlphaZero on Strongly-Solved Stochastic Games Open
The AlphaZero algorithm achieved superhuman levels of play in chess, shogi, and Go by learning without domain-specific knowledge except for game rules. This paper targets stochastic games and investigates whether AlphaZero can learn theore…