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Found 16 papers, 7 papers with code
ULTRA: Unleash LLMs' Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Refinement
Event argument extraction (EAE), at the core of event-centric understanding, is the task of identifying role-specific text spans (i. e., arguments) for a given event.
Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
For example, on sentiment classification using the SST-2 dataset, our method improves the adversarial accuracy over the best existing defense approach by more than 4% with a smaller decrease in task accuracy (0. 5% vs 2. 5%).
Multi-Task Triplet Loss for Named Entity Recognition using Supplementary Text
Retail item data contains many different forms of text like the title of an item, the description of an item, item name and reviews.
Comparison of Stochastic Forecasting Models
In this work, we compare several stochastic forecasting techniques like Stochastic Differential Equations (SDE), ARIMA, the Bayesian filter, Geometric Brownian motion (GBM), and the Kalman filter.
Multi-Task Learning of Query Intent and Named Entities using Transfer Learning
Task specific NER has two components - identifying the intent of a piece of text (like search queries), and then labeling the query with task specific named entities.
GCLIQUE: An Open Source Genetic Algorithm for the Maximum Clique Problem
In this work, we present a genetic algorithm for the maximum clique problem that is able to find optimum or close to optimum solutions to most DIMACS graphs.
Simulated Annealing Algorithm for the Multiple Choice Multidimensional Knapsack Problem
In this work, we present a simulated annealing based algorithm with open source C++ code to find good solutions to the multidimensional multiple choice knapsack problem.
JCOL: A Java package for solving the graph coloring problem
The graph coloring problem aims at assigning colors to the nodes of a graph such that no two connected nodes have the same color.
Analysis of Greenhouse Gases
Because of the uptake mechanism of the land and ocean, greenhouse gas emissions can take a while to affect the climate.
Hebbian Graph Embeddings
Representation learning has recently been successfully used to create vector representations of entities in language learning, recommender systems and in similarity learning.
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm.
Genetic Algorithm for the 0/1 Multidimensional Knapsack Problem
The 0/1 multidimensional knapsack problem is the 0/1 knapsack problem with m constraints which makes it difficult to solve using traditional methods like dynamic programming or branch and bound algorithms.
Genetic Algorithm for a class of Knapsack Problems
The 0/1 knapsack problem is weakly NP-hard in that there exist pseudo-polynomial time algorithms based on dynamic programming that can solve it exactly.
Randomized heuristic for the maximum clique problem
Finding the maximum clique in a graph is an NP-hard problem and it cannot be solved by an approximation algorithm that returns a solution within a constant factor of the optimum.
Implementation of iterative local search (ILS) for the quadratic assignment problem
The quadratic assignment problem (QAP) is one of the hardest NP-hard problems and problems with a dimension of 20 or more can be difficult to solve using exact methods.
DNACloud: A Potential Tool for storing Big Data on DNA
However before one can use the data, one has to address many issues for big data storage.
Emerging Technologies
