Model Detail
lift
—lift is a multimodal model with 4.8B parameters released by datalab-to. The model is registered under the image-text-to-text pipeline tag on Hugging Face, released under the openrail license.
lift ships with 4.8B parameters. Total weight footprint is approximately 9.7 GB, which is the relevant figure when planning local-inference VRAM. Distribution is governed by the openrail license — review the exact terms before commercial deployment.
lift is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
LIFT: Likelihood-Based Intervention Faithfulness Training
arXiv:2509.13334v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning improves LLM accuracy on complex tasks, but CoTs are often unfaithful; that is, the model does not rely on the stated reasoning steps to produce its answer. Existing methods to improve faithfulness require human ann
Batch Before You Lift: Scalable Topological Deep Learning on Large Graphs
arXiv:2610.12247v1 Announce Type: cross Abstract: Topological Deep Learning extends graph-based learning to higher-order domains, such as hypergraphs, cellular, and simplicial complexes. These domains are typically constructed from patterns in an input graph through a process of graph lifting. Full-
Quantifying Diversity of Thought: A Predictive Law of Weighted LLM Ensemble Lift
arXiv:2607.17384v3 Announce Type: replace-cross Abstract: This paper provides an experimentally verified formal law for calculating the uplift that diversity of thought provides in Large Language Model (LLM) ensembles. From first principles, we derive an exact decomposition of LLM ensemble lift into
HiLiftAeroML: A High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics
arXiv:2605.19565v2 Announce Type: replace-cross Abstract: HiLiftAeroML is, to our knowledge, the first open high-fidelity computational fluid dynamics dataset dedicated to high-lift aircraft aerodynamics. It contains 1,800 simulations spanning 180 variants of the NASA Common Research Model high-lift
A lift for input-convex neural net training
arXiv:2605.24274v2 Announce Type: replace Abstract: Input-convex neural nets parametrize the convex potentials of density models and transport maps, and their convexity requires the inter-layer weights to be non-negative. Projected gradient descent enforces this by projecting after each step, and du
Towards simultaneous decoding of kinetic and kinematic movement parameters during grasp and lift task by noninvasive brain imaging
arXiv:2607.24081v2 Announce Type: replace-cross Abstract: Brain-machine interfaces (BMIs) can assist individuals with limited mobility, such as stroke survivors or amputees. One of the key challenges in developing BMIs is expanding their usability and control, which can be achieved by accurately dec
