Introduces LOES, a constructive spectral method to select task-discriminative subspaces from intermediate layer embeddings, and GeoReg for enforcing simplicial class geometry during fine-tuning, with reported gains increasing with model depth across modalities.
Efficient Intent Detection with Dual Sentence Encoders , url =
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Many-shot CoT-ICL improves when demonstrations are ordered for smooth conceptual progression, with CDS delivering up to 5.42 percentage-point gains on math tasks using 64 examples.
Truncated embeddings from non-MRL models perform comparably to or better than MRL-trained models for most truncation levels, except heavy truncation of 80% or more.
citing papers explorer
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Uncovering the Latent Potential of Deep Intermediate Representations
Introduces LOES, a constructive spectral method to select task-discriminative subspaces from intermediate layer embeddings, and GeoReg for enforcing simplicial class geometry during fine-tuning, with reported gains increasing with model depth across modalities.
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Many-Shot CoT-ICL: Making In-Context Learning Truly Learn
Many-shot CoT-ICL improves when demonstrations are ordered for smooth conceptual progression, with CDS delivering up to 5.42 percentage-point gains on math tasks using 64 examples.
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To MRL or not to MRL: Text Embeddings are Robust to Truncation Without Matryoshka Learning, Except In Heavy Truncation Scenarios
Truncated embeddings from non-MRL models perform comparably to or better than MRL-trained models for most truncation levels, except heavy truncation of 80% or more.