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