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20212026
most citedOCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Tracing the Arrow of Time: Diagnosing Temporal Information Flow in Video-LLMs

Peitao Han, Fei Cheng, Lis K. Pereira +2

The Arrow-of-Time (AoT) task, determining whether a video plays forward or backward by recognizing temporal irreversibility, is one humans solve with near-perfect accuracy, yet fro…

cs.CL2026

EmplifAI: a Fine-grained Dataset for Japanese Empathetic Medical Dialogues in 28 Emotion Labels

Wan Jou She, Lis Kanashiro Pereira, Fei Cheng +3

This paper introduces EmplifAI, a Japanese empathetic dialogue dataset designed to support patients coping with chronic medical conditions. They often experience a wide range of po…

cs.CV2025

Which Way Does Time Flow? A Psychophysics-Grounded Evaluation for Vision-Language Models

Shiho Matta, Lis Kanashiro Pereira, Peitao Han +2

Modern vision-language models (VLMs) excel at many multimodal tasks, yet their grasp of temporal information in video remains weak and has not been adequately evaluated. We probe t…

cs.CL2024

AMR-RE: Abstract Meaning Representations for Retrieval-Based In-Context Learning in Relation Extraction

Peitao Han, Lis Kanashiro Pereira, Fei Cheng +2

Existing in-context learning (ICL) methods for relation extraction (RE) often prioritize language similarity over structural similarity, which can lead to overlooking entity relati…

cs.CL2021★ 1 cited

OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction

Yuki Taya, Lis Kanashiro Pereira, Fei Cheng +1

We propose an ensemble model for predicting the lexical complexity of words and multiword expressions (MWEs). The model receives as input a sentence with a target word or MWEand ou…