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Found 5 papers, 1 papers with code
Decoding Continuous Character-based Language from Non-invasive Brain Recordings
Deciphering natural language from brain activity through non-invasive devices remains a formidable challenge.
Advancing Parameter Efficiency in Fine-tuning via Representation Editing
Parameter Efficient Fine-Tuning (PEFT) has gained significant attention for its ability to achieve competitive results while updating only a small subset of trainable parameters.
Aligning Large Language Models with Human Preferences through Representation Engineering
Aligning large language models (LLMs) with human preferences is crucial for enhancing their utility in terms of helpfulness, truthfulness, safety, harmlessness, and interestingness.
Tailoring Personality Traits in Large Language Models via Unsupervisedly-Built Personalized Lexicons
Users can utilize UBPL to adjust the probability vectors of predicted words in the decoding phase of LLMs, thus influencing the personality expression of LLMs.
SpikeBERT: A Language Spikformer Learned from BERT with Knowledge Distillation
Spiking neural networks (SNNs) offer a promising avenue to implement deep neural networks in a more energy-efficient way.
