COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
Towards better instruction following language models for chinese: Investigating the im- pact of training data and evaluation
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DuplexOmni achieves real-time full-duplex multimodal interaction by separating an interaction layer from a pluggable thinking layer, supported by a Writer-Director pipeline for continuous-interaction training data.
This survey reviews the background, key techniques, and evaluation methods for large language models, emphasizing emergent abilities that appear at large scales.
citing papers explorer
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COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling
COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
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DuplexOmni: Real-Time Listening, Seeing, Thinking, and Speaking for Full-Duplex Interaction
DuplexOmni achieves real-time full-duplex multimodal interaction by separating an interaction layer from a pluggable thinking layer, supported by a Writer-Director pipeline for continuous-interaction training data.
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A Survey of Large Language Models
This survey reviews the background, key techniques, and evaluation methods for large language models, emphasizing emergent abilities that appear at large scales.