2 citations · 5 across the 9 of their papers we have counts for
10 papers · 1 filter
When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression
Riku Kisako, Hayato Tsukagoshi, Ryohei Sasano
Recent high-performing text embedding models often produce high-dimensional real-valued vectors, resulting in substantial storage and computational costs. To address this issue, em…
FrameEOL: Semantic Frame Induction using Causal Language Models
Chihiro Yano, Kosuke Yamada, Hayato Tsukagoshi +2
Semantic frame induction is the task of clustering frame-evoking words according to the semantic frames they evoke. In recent years, leveraging embeddings of frame-evoking words th…
Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings
Hayato Tsukagoshi, Ryohei Sasano
Prompt-based text embedding models, which generate task-specific embeddings upon receiving tailored prompts, have recently demonstrated remarkable performance. However, their resul…
Ruri: Japanese General Text Embeddings
Hayato Tsukagoshi, Ryohei Sasano
We report the development of Ruri, a series of Japanese general text embedding models. While the development of general-purpose text embedding models in English and multilingual co…
WikiSplit++: Easy Data Refinement for Split and Rephrase
Hayato Tsukagoshi, Tsutomu Hirao, Makoto Morishita +3
The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstrea…
Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot Examples
Soma Sato, Hayato Tsukagoshi, Ryohei Sasano +1
Decoder-based large language models (LLMs) have shown high performance on many tasks in natural language processing. This is also true for sentence embedding learning, where a deco…
Japanese SimCSE Technical Report
Hayato Tsukagoshi, Ryohei Sasano, Koichi Takeda
We report the development of Japanese SimCSE, Japanese sentence embedding models fine-tuned with SimCSE. Since there is a lack of sentence embedding models for Japanese that can be…
Sentence Representations via Gaussian Embedding
Shohei Yoda, Hayato Tsukagoshi, Ryohei Sasano +1
Recent progress in sentence embedding, which represents the meaning of a sentence as a point in a vector space, has achieved high performance on tasks such as a semantic textual si…
Comparison and Combination of Sentence Embeddings Derived from Different Supervision Signals
Hayato Tsukagoshi, Ryohei Sasano, Koichi Takeda
There have been many successful applications of sentence embedding methods. However, it has not been well understood what properties are captured in the resulting sentence embeddin…
DefSent: Sentence Embeddings using Definition Sentences
Hayato Tsukagoshi, Ryohei Sasano, Koichi Takeda
Sentence embedding methods using natural language inference (NLI) datasets have been successfully applied to various tasks. However, these methods are only available for limited la…