Implementation of the paper Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs🔔 News🎉 [2024-12-10]: Released the code for SVE-Math-Qwen2.5-7B. 🎉 [2024-12-12]: Released model weights of GeoGLIP. 🎉 [2024-12-26]: Released model weights of SVE-Math...
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The second activity resulted in a table of knowledge areas with minimum and maximum weights for six computing subdisciplines. Finally, this paper also shows two examples of how users can explore the various curricular guidelines through visualization....
Paper Universal Multimodal Representation for Language Understanding Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP tasks. For each sentence, we first retrieve a flexible number...
In the first stage, we prompt the MLLM to locate the approximate area of the answer. In the second stage, we further enhance the model's focus on relevant areas within the image through visual prompt engineering, adjusting attention weights of pertinent regions. This, in turn, improves both...
This position paper argues for the use of structured generative models (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view images), whereby the contents of the image(s) are causally explained in terms of...
(3,2)# initialize weights and biasesself.lin1.weight=nn.Parameter(torch.arange(-4.0,5.0).view(3,3))self.lin1.bias=nn.Parameter(torch.zeros(1,3))self.lin2.weight=nn.Parameter(torch.arange(-3.0,3.0).view(2,3))self.lin2.bias=nn.Parameter(torch.ones(1,2))defforward(self,input):...
The global multi-view feature P∈R1×N are defined as: (8)P=fc⋅w+δ⋅fc⋅β,The weight w∈R1×N, δ∈R1×N and β∈R1 are employed to fine-tune the weights of fc∈R1×N. The unlearnable hyperparameter β serves as the balance factor for the residual connection, similar to...
Similarly, firms or managers may employ subjectivity during the period or on an ex post basis to revise targets, change the relative weights on performance measures used to evaluate overall performance, or incorporate other factors (e.g., uncontrollable events). Absent valid measures of employees’...
delete--pretrain_mm_mlp_adapterbecause we load the cross-modality projector from merged weights customize the hyperparameters, e.g. the learning rate, to fit your dataset Please note thatif you continuously fine-tune SpatialBot using LoRA,--model-baseshould be SpatialBot models rather than the...