Designing an automatic solver for math word problems has been considered as a crucial step towards general AI, with the ability of natural language understanding and logical inference. The state-of-the-art perf
[AllArith]Unit dependency graph and its application to arithmetic word problem solving, AAAI 2017 [paper] [DRAW-1K]Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems, ACL 2017 [paper] 🔥 [Math23K]Deep neural solver for math word problems, EMNLP 2017 [pape...
Interestingly, deep learning algorithms have been used as surrogate models for solving such regression problems. For instance, the surrogate method, which is trained on sample points, has been used in the evolution algorithm (EA) to reduce the computational cost for functional evaluations (FEs) to ...
For tasks such as complex math, factual queries, or code execution, calling specialized tools can dramatically improve reliability. Studies show that augmenting GPT-4 with a math solver (Wolfram Alpha) or a Python execution plugin significantly enhances problem-solving performance on challenging science...
Safety concerns on the deep neural networks (DNNs) have been raised when they are applied to critical sectors. In this paper, we define safety risks by req
). So automatically we learn 32 new features that have relevant information for our task in them. These feature then provide the inputs for the next kernel which filters the inputs again. Once we learned our hierarchical features, we simply pass them to a fully connected, simple neural netwo...
we applied random under-sampling as the balancing method. Thirty-two different combinations were used as features that have been mentioned already. To set the neural networks: the number of batch sizes for MLP and CNN were 310 and 16, respectively. Additionally, the number of epochs was determi...
Mathematically, each layer of a neural network is given through computing the activation function,$\basisFunction(\cdot)$, contingent on the previous layer, or the inputs. In this way the activation functions, are composed to generate more complex interactions than would be possible with any sing...
Concurrently, we built a geometric problem solver (FGPS) to validate annotated theorem sequences. By annotating the original image and text information of problems into a form understandable by the geometric formal language system, we can input the theorem sequences for validation. This not only ...
"Instead of formally defining the optimization problem and deriving the update step with a programmed solver," the researchers write, "we describe the optimization problem in natural language, then instruct the LLM to iteratively generate new solutions based on the problem ...