8 citations · 25 across the 17 of their papers we have counts for
11 papers · 1 filter
When Modality Gap Reduction Fails: Prediction-Level Hubness in CLIP
Shota Sato, Hajime Kiyama, Tosho Hirasawa +1
Reducing the modality gap between image and text representations in CLIP is widely expected to improve cross-modal alignment and downstream performance. However, a smaller average…
Am I More Pointwise or Pairwise? Revealing Position Bias in Rubric-Based LLM-as-a-Judge
Yuzheng Xu, Tosho Hirasawa, Tadashi Kozuno +1
Large language models are widely employed as evaluators, a paradigm commonly referred to as LLM-as-a-judge. Prior research has predominantly examined point-wise or pair-wise evalua…
WarrantScore: Modeling Warrants between Claims and Evidence for Substantiation Evaluation in Peer Reviews
Kiyotada Mori, Shohei Tanaka, Tosho Hirasawa +3
The scientific peer-review process is facing a shortage of human resources due to the rapid growth in the number of submitted papers. The use of language models to reduce the human…
Assessing the Capabilities of LLMs in Humor:A Multi-dimensional Analysis of Oogiri Generation and Evaluation
Ritsu Sakabe, Hwichan Kim, Tosho Hirasawa +1
Computational humor is a frontier for creating advanced and engaging natural language processing (NLP) applications, such as sophisticated dialogue systems. While previous studies…
MK2 at PBIG Competition: A Prompt Generation Solution
Yuzheng Xu, Tosho Hirasawa, Seiya Kawano +2
The Patent-Based Idea Generation task asks systems to turn real patents into product ideas viable within three years. We propose MK2, a prompt-centric pipeline: Gemini 2.5 drafts a…
Pruning Multilingual Large Language Models for Multilingual Inference
Hwichan Kim, Jun Suzuki, Tosho Hirasawa +1
Multilingual large language models (MLLMs), trained on multilingual balanced data, demonstrate better zero-shot learning performance in non-English languages compared to large lang…
Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction
Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita +5
In grammatical error correction (GEC), automatic evaluation is an important factor for research and development of GEC systems. Previous studies on automatic evaluation have demons…
Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020
Tosho Hirasawa, Zhishen Yang, Mamoru Komachi +1
Video-guided machine translation as one of multimodal neural machine translation tasks targeting on generating high-quality text translation by tangibly engaging both video and tex…
Towards Multimodal Simultaneous Neural Machine Translation
Aizhan Imankulova, Masahiro Kaneko, Tosho Hirasawa +1
Simultaneous translation involves translating a sentence before the speaker's utterance is completed in order to realize real-time understanding in multiple languages. This task is…
Debiasing Word Embeddings Improves Multimodal Machine Translation
Tosho Hirasawa, Mamoru Komachi
In recent years, pretrained word embeddings have proved useful for multimodal neural machine translation (NMT) models to address the shortage of available datasets. However, the in…
Multimodal Machine Translation with Embedding Prediction
Tosho Hirasawa, Hayahide Yamagishi, Yukio Matsumura +1
Multimodal machine translation is an attractive application of neural machine translation (NMT). It helps computers to deeply understand visual objects and their relations with nat…