5 papers
CORTEX: Token-Level Hallucination Detection in RAG via Comparative Internal Representations
Kazuaki Furumai, Shuichiro Haruta, Kazunori Matsumoto +1
In this paper, we propose CORTEX, a token-level hallucination detection method for Retrieval-Augmented Generation (RAG). In long-form RAG outputs, hallucinations often arise in loc…
Algebraic Quantum Intelligence: A New Framework for Reproducible Machine Creativity
Kazuo Yano, Jonghyeok Lee, Tae Ishitomi +26
Large language models (LLMs) have achieved remarkable success in generating fluent and contextually appropriate text; however, their capacity to produce genuinely creative outputs…
CADE: Continual Weakly-supervised Video Anomaly Detection with Ensembles
Satoshi Hashimoto, Tatsuya Konishi, Tomoya Kaichi +2
Video anomaly detection (VAD) has long been studied as a crucial problem in public security and crime prevention. In recent years, weakly-supervised VAD (WVAD) have attracted consi…
RCPU: Rotation-Constrained Error Compensation for Structured Pruning of Large Language Models
Shuichiro Haruta, Kazunori Matsumoto, Zhi Li +2
In this paper, we propose a rotation-constrained compensation method to address the errors introduced by structured pruning of large language models (LLMs). LLMs are trained on mas…
Topic-switch adapted Japanese Dialogue System based on PLATO-2
Donghuo Zeng, Jianming Wu, Yanan Wang +3
Large-scale open-domain dialogue systems such as PLATO-2 have achieved state-of-the-art scores in both English and Chinese. However, little work explores whether such dialogue syst…