2 citations · 2 across the 1 of their papers we have counts for
7 papers
Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models
Sangwhan Moon, Daisuke Oba, Youmi Ma +2
Byte-level tokenization enables language models to handle any Unicode input, but models can generate invalid UTF-8 sequences when encountering rare or unseen characters. We investi…
From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models
Youmi Ma, Naoaki Okazaki
Advances in mechanistic interpretability have identified special attention heads, known as retrieval heads, that are responsible for retrieving information from the context. Howeve…
QuantumBench: A Benchmark for Quantum Problem Solving
Shunya Minami, Tatsuya Ishigaki, Ikko Hamamura +6
Large language models are now integrated into many scientific workflows, accelerating data analysis, hypothesis generation, and design space exploration. In parallel with this grow…
Machine Text Detectors are Membership Inference Attacks
Ryuto Koike, Liam Dugan, Masahiro Kaneko +2
Although membership inference attacks (MIAs) and machine-generated text detection target different goals, their methods often exploit similar signals based on a language model's pr…
Intent-Aware Self-Correction for Mitigating Social Biases in Large Language Models
Panatchakorn Anantaprayoon, Masahiro Kaneko, Naoaki Okazaki
Self-Correction based on feedback improves the output quality of Large Language Models (LLMs). Moreover, as Self-Correction functions like the slow and conscious System-2 thinking…
ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability
Ryuto Koike, Masahiro Kaneko, Ayana Niwa +2
Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' academic dignity. LLM text detection…