6 papers
Language Reconstruction with Brain Predictive Coding from fMRI Data
Congchi Yin, Ziyi Ye, Piji Li
Many recent studies have shown that the perception of speech can be decoded from brain signals and subsequently reconstructed as continuous language. However, there is a lack of ne…
From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance
Runze Xia, Yupeng Ji, Yuxi Zhou +3
Query-service relevance prediction in e-commerce search systems faces strict latency requirements that prevent the direct application of Large Language Models (LLMs). To bridge thi…
Rethinking Cross-Subject Data Splitting for Brain-to-Text Decoding
Congchi Yin, Qian Yu, Zhiwei Fang +2
Recent major milestones have successfully reconstructed natural language from non-invasive brain signals (e.g. functional Magnetic Resonance Imaging (fMRI) and Electroencephalogram…
Improving Brain-to-Image Reconstruction via Fine-Grained Text Bridging
Runze Xia, Shuo Feng, Renzhi Wang +3
Brain-to-Image reconstruction aims to recover visual stimuli perceived by humans from brain activity. However, the reconstructed visual stimuli often missing details and semantic i…
Improve Language Model and Brain Alignment via Associative Memory
Congchi Yin, Yongpeng Zhang, Xuyun Wen +1
Associative memory engages in the integration of relevant information for comprehension in the human cognition system. In this work, we seek to improve alignment between language m…
MDD-5k: A New Diagnostic Conversation Dataset for Mental Disorders Synthesized via Neuro-Symbolic LLM Agents
Congchi Yin, Feng Li, Shu Zhang +5
The clinical diagnosis of most mental disorders primarily relies on the conversations between psychiatrist and patient. The creation of such diagnostic conversation datasets is pro…