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Found 5 papers, 2 papers with code
Model Utility Law: Evaluating LLMs beyond Performance through Mechanism Interpretable Metric
One core challenge of evaluation in the large language model (LLM) era is the generalization issue: how to infer a model's near-unbounded abilities from inevitably bounded benchmarks.
EvoWiki: Evaluating LLMs on Evolving Knowledge
Knowledge utilization is a critical aspect of LLMs, and understanding how they adapt to evolving knowledge is essential for their effective deployment.
Federated Instruction Tuning of LLMs with Domain Coverage Augmentation
Our experiments reveal that the cross-client domain coverage, rather than data heterogeneity, drives model performance in FedDIT.
RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models
Uni-Food is designed to provide a more holistic approach to food data analysis, thereby enhancing the performance and capabilities of LMMs in this domain.
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images, and music.
