#Japan #Tokyo #Language Models #Omron Sinicx #NAACL2025

Omron SinicX to Showcase Research at NAACL2025

Omron SinicX, a leading innovator in the field of artificial intelligence and natural language processing, is excited to announce its participation in the upcoming 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL2025). This esteemed conference will take place in New Mexico from April 29 to May 4, 2025. At NAACL2025, Omron SinicX will unveil its latest research findings, presenting a groundbreaking paper titled, "Where is the answer? An empirical study of positional bias for parametric knowledge extraction in language models."

Insights from the Research

The paper, co-authored by Kuniaki Saito from Omron SinicX, along with researchers from Google Cloud AI and Google Research, delves into the intricate processes by which language models store and retrieve information. It highlights the significance of unsupervised learning using unlabeled text data, which empowers these models to acquire a wide range of knowledge. However, the extraction of accurate responses to specific queries from the model's parameters remains a formidable challenge.

A critical focus of the study is the phenomenon known as the perplexity curse. This term describes the difficulty encountered when training models to minimize loss on training data, but failing to generate precise answers to actual questions when tested in real-world scenarios.

The research identifies positional bias within the training data as a significant contributor to this perplexity curse. Specifically, it reveals that language models often struggle to provide accurate answers for information positioned towards the middle or end of the training data. Additionally, the findings suggest that the issue is tied closely to the auto-regressive learning technique, which predicts the next token based on the previous ones. This discovery presents critical implications for enhancing the efficiency of knowledge extraction from language model parameters.

Future Impact and Collaboration

Through this exploration, Omron SinicX aims to open new pathways for improving knowledge retrieval mechanisms in language models. Such advancements not only enhance the models’ utility but also highlight the innovative spirit prevalent at Omron SinicX. As a strategic hub for advancing near-future design, the company combines cutting-edge technologies like AI, robotics, IoT, and sensing to address societal challenges. Omron SinicX is committed to forging collaborative research endeavors with universities and external research institutions to accelerate the development of future-oriented solutions.

Learn More

For more information about the research and activities of Omron SinicX, you can visit their official website at Omron SinicX or check their latest updates at Latest Activities.

Please note that affiliations may differ from those at the time of writing. Future developments can alter this information, so it’s advisable to verify the details accordingly.