6 citations · 30 across the 37 of their papers we have counts for
6 papers · 1 filter
Rethinking Least-Core Computation in Contextual-Distractor Games
Hiroshi Kera, Toshinori Yamauchi, Sai Ganesh Nagarajan
Game-theoretic attribution explains a model by assigning credit to its features or training examples. The least core has attracted interest as an alternative to Shapley-style avera…
What Does Prompt Learning Change? -A Natural-Language Concept Analysis of Vision-Language Models
Ryo Kamiya, Hiroshi Kera, Kazuhiko Kawamoto
Prompt learning adapts vision-language models such as CLIP by optimizing continuous prompt vectors, but the learned prompts are difficult to interpret in natural language. We prese…
Zero-Shot Faithful Textual Explanations via Directional-Derivative Influence on Predictions
Toshinori Yamauchi, Hiroshi Kera, Kazuhiko Kawamoto
Zero-shot textual explanations aim to make image classifiers more transparent by probing their internal representations, without relying on task-specific supervision or LVLMs. Howe…
Guided Diffusion Sampling for Precipitation Forecast Interventions
Ayumu Ueyama, Kazuhiko Kawamoto, Hiroshi Kera
Extreme precipitation causes severe societal and economic damage, and weather control has long been discussed as a potential mitigation strategy. However, to the best of our knowle…
Learning Large-Scale Modular Addition with an Auxiliary Modulus
Hanato Kikuchi, Ryosuke Masuya, Kazuhiko Kawamoto +1
Learning parity functions, more general modular addition, is a challenging machine learning task due to its input sensitivity. A recent study substantially scaled modular addition…
Robust Human Trajectory Prediction via Self-Supervised Skeleton Representation Learning
Taishu Arashima, Hiroshi Kera, Kazuhiko Kawamoto
Human trajectory prediction plays a crucial role in applications such as autonomous navigation and video surveillance. While recent works have explored the integration of human ske…