1 citations · 2 across the 9 of their papers we have counts for
9 papers
Integrating Multi-Source Feedback in Computational Design
Francisco Erivaldo Fernandes Junior, Thomas Langerak, Mira Keränen +3
In real-world design practice, evaluations rarely rely on a single source of judgment. Designers routinely combine expert opinions, empirical studies, and computational models, eac…
Hierarchical Resource Rationality Explains Human Reading Behavior
Yunpeng Bai, Xiaofu Jin, Shengdong Zhao +1
Reading is a pervasive and cognitively demanding activity that underpins modern human culture. It is a prime instance of a class of tasks where eye movements are coordinated for th…
DxHF: Providing High-Quality Human Feedback for LLM Alignment via Interactive Decomposition
Danqing Shi, Furui Cheng, Tino Weinkauf +2
Human preferences are widely used to align large language models (LLMs) through methods such as reinforcement learning from human feedback (RLHF). However, the current user interfa…
Interactive Groupwise Comparison for Reinforcement Learning from Human Feedback
Jan Kompatscher, Danqing Shi, Giovanna Varni +2
Reinforcement learning from human feedback (RLHF) has emerged as a key enabling technology for aligning AI behaviour with human preferences. The traditional way to collect data in…
ChartOptimiser: Task-driven Optimisation of Chart Designs
Yao Wang, Jiarong Pan, Danqing Shi +3
Automated chart design has seen significant advancements with the emergence of Large-Language Models (LLMs), which offer a practical solution for generating charts. However, LLMs f…
Chartist: Task-driven Eye Movement Control for Chart Reading
Danqing Shi, Yao Wang, Yunpeng Bai +2
To design data visualizations that are easy to comprehend, we need to understand how people with different interests read them. Computational models of predicting scanpaths on char…
Simulating Errors in Touchscreen Typing
Danqing Shi, Yujun Zhu, Francisco Erivaldo Fernandes Junior +2
Empirical evidence shows that typing on touchscreen devices is prone to errors and that correcting them poses a major detriment to users' performance. Design of text entry systems…
WigglyEyes: Inferring Eye Movements from Keypress Data
Yujun Zhu, Danqing Shi, Hee-Seung Moon +1
We present a model for inferring where users look during interaction based on keypress data only. Given a key log, it outputs a scanpath that tells, moment-by-moment, how the user…
AgentForge: A Flexible Low-Code Platform for Reinforcement Learning Agent Design
Francisco Erivaldo Fernandes Junior, Antti Oulasvirta
Developing a reinforcement learning (RL) agent often involves identifying values for numerous parameters, covering the policy, reward function, environment, and agent-internal arch…