Towards Understanding Extrapolation: a Causal Lens
Authors: Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric Xing, Kun Zhang
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Through experiments on both synthetic and real-world data, we validate our theoretical findings and their practical implications. |
| Researcher Affiliation | Academia | 1 Carnegie Mellon University 2 Mohamed bin Zayed University of Artificial Intelligence 3 Broad Institute of MIT and Harvard, Cancer Program, Eric and Wendy Schmidt Center |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | Yes | The code is provided here. |
| Open Datasets | Yes | We conduct experiments on Image Net-C [45] and Image Net100-C [46] with 15 different types of corruption. ...We conduct experiments on the CIFAR10-C, CIFAR100-C, and Image Net-C datasets [45]... |
| Dataset Splits | No | The paper mentions training and testing, but does not explicitly provide details about a validation dataset split (e.g., percentages or sample counts for validation). |
| Hardware Specification | Yes | The experiments are conducted with the Py Torch 1.11.0 framework, CUDA 12.0 with 4 NVIDIA A100 GPUs. ... The experiments are conducted with the Py Torch 1.13.0 framework, CUDA 11.7 with an NVIDIA A100 GPU. |
| Software Dependencies | Yes | The experiments are conducted with the Py Torch 1.11.0 framework, CUDA 12.0 with 4 NVIDIA A100 GPUs. ... The experiments are conducted with the Py Torch 1.13.0 framework, CUDA 11.7 with an NVIDIA A100 GPU. |
| Experiment Setup | Yes | We train all methods with Adam [68] and learning rate 2e 3 for 25 epochs. We fix the loss weights λcls = 1, λrecons = 0.1, λtgt_likelihood = 0.1, and λs_distance = 0.01 (for dense shifts) overall distance configurations. We only tune λKL from the interval {1e 1, 1e 2, 1e 3}. ... In the pre-train stage, we apply the Res Net50 [47] as the backbone network... |