Asia
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Even in large language models, negative transfer problems may still exist.
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Even in large language models, negative transfer problems may still exist.
DATA: Differentiable ArchiTecture Approximation
Jianlong Chang, xinbang zhang, Yiwen Guo, GAOFENG MENG, SHIMING XIANG, Chunhong Pan
Neural Information Processing Systems http://nips.cc/
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD Xiaoyi Dong
The Large Vision-Language Model (L VLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due to limited resolution.
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten, Jouni Helske, Matti Vihola
Neural Information Processing Systems http://nips.cc/
Constrained Cross-Entropy Method for Safe Reinforcement Learning
Neural Information Processing Systems http://nips.cc/
Fair Infinitesimal Jackknife: Mitigatingthe Influence of Biased Training Data Points Without Refitting
Algorithm 2 (see Appendix) summarizesourvanillaapproach.