activity
20232026
most citedJVNV: A Corpus of Japanese Emotional Speech with Verbal Content and Nonverbal Expressions

21 citations · 26 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

FlexComp: One Model for Every Ratio in Context Compression

Kaiyan Zhao, Zhongtao Miao, Akiko Aizawa +1

Soft context compression condenses a context into a few memory tokens that a frozen LLM consumes in place of the raw text, but existing compressors fix the compression ratio at tra…

cs.CL2026

RegMix-D: Dynamic Data Mixing via Proxy Training Trajectories

Kaiyan Zhao, Zhongtao Miao, Akiko Aizawa +1

Data mixture selection is critical for Large Language Model pretraining. Existing methods such as RegMix select a single static mixture by fitting a regression model on small-scale…

cs.AI2026

Tailoring the Curriculum: Student-Centered Reasoning Distillation via Dynamic Data-Model Compatibility

Jiahao Huang, Fei Cheng, Junfeng Jiang +1

Reasoning distillation transfers complex reasoning abilities from large language models (LLMs) to smaller ones, yet its success depends on how well the training data align with the…

cs.AI2026

BenchTrace: A Benchmark for Testing Reflection Ability and Controlled Evolution in LLM Agents

Jiahao Huang, Fei Cheng, Junfeng Jiang +2

Self-evolving agents improve over time by reflecting on past failures, but existing evaluation is limited in two ways: it measures only task scores, leaving reflection quality unkn…

cs.CL2024

JMedBench: A Benchmark for Evaluating Japanese Biomedical Large Language Models

Junfeng Jiang, Jiahao Huang, Akiko Aizawa

Recent developments in Japanese large language models (LLMs) primarily focus on general domains, with fewer advancements in Japanese biomedical LLMs. One obstacle is the absence of…

cs.CL2024

MoreHopQA: More Than Multi-hop Reasoning

Julian Schnitzler, Xanh Ho, Jiahao Huang +3

Most existing multi-hop datasets are extractive answer datasets, where the answers to the questions can be extracted directly from the provided context. This often leads models to…

cs.IR2024

TWOLAR: a TWO-step LLM-Augmented distillation method for passage Reranking

Davide Baldelli, Junfeng Jiang, Akiko Aizawa +1

In this paper, we present TWOLAR: a two-stage pipeline for passage reranking based on the distillation of knowledge from Large Language Models (LLM). TWOLAR introduces a new scorin…

cs.CL2024★ 4 cited

A Survey of Pre-trained Language Models for Processing Scientific Text

Xanh Ho, Anh Khoa Duong Nguyen, An Tuan Dao +6

The number of Language Models (LMs) dedicated to processing scientific text is on the rise. Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task…

cs.CL2023★ 1 cited

Solving Label Variation in Scientific Information Extraction via Multi-Task Learning

Dong Pham, Xanh Ho, Quang-Thuy Ha +1

Scientific Information Extraction (ScientificIE) is a critical task that involves the identification of scientific entities and their relationships. The complexity of this task is…

cs.SD2023★ 21 cited

JVNV: A Corpus of Japanese Emotional Speech with Verbal Content and Nonverbal Expressions

Detai Xin, Junfeng Jiang, Shinnosuke Takamichi +3

We present the JVNV, a Japanese emotional speech corpus with verbal content and nonverbal vocalizations whose scripts are generated by a large-scale language model. Existing emotio…