Proves theorem about meromorphic projective structures with complex poles.
problem Proving a theorem about meromorphic projective structures with complex poles.
method Using coordinates on the moduli space of framed representations from Fock and Goncharov.
result Proves the analogue of a theorem of Gallo-Kapovich-Marden.
Characterizes monodromy groups for projective structures on surfaces with specified poles.
problem Characterizing monodromy groups for meromorphic projective structures on surfaces with specific singularities.
method Geometric interpretation of Fock-Goncharov coordinates and recent results on moduli spaces of representations.
result Proves the analogue of a theorem for closed surfaces and settles a long-standing question.
The article extends Thurston's Grafting Theorem to signed spaces and defines a framed monodromy map.
problem Extending Thurston's Grafting Theorem to signed spaces.
method Proves the analogue of Thurston's Grafting Theorem for signed spaces, defines a framed monodromy map.
result Characterizes PSL(2,C)-representations and shows the monodromy map is a local biholomorphism.
Hybrid QC system for Bengali questions using smart data balancing.
problem Classifying factoid questions in Bengali.
method Two-stage approach with 1D CNN for coarse classification and SGD for fine classification.
result Effectiveness of smart data balancing technique in improving classification accuracy.
We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers. Generating these questions can be difficult without trading away originality, relevance or diversity in the answer options. Our method addresses these problems by leveraging a large corpus of domain-speci…
Paper tackles medical question similarity using domain-relevant embeddings.
problem Identifying same-question pairs in medical contexts.
method Semi-supervised pre-training of a neural network on medical question-answer pairs.
result Our model achieves 82.6% accuracy on medical question similarity task.
Paper analyzes biases in video QA datasets, showing models can answer 37-48% questions correctly without multimodal context.
problem Question answering biases in video QA datasets can lead to model overfitting and poor generalization.
method Analyzed popular video question answering datasets, conducted ablation studies on biases from annotators and question types.
result Pretrained language models can answer 37-48% questions correctly without multimodal context, far exceeding random guess baseline.
Paper evaluates Arabic question similarity, 9 teams participated.
problem Predicting semantic similarity between Arabic questions.
method 9 teams participated in a shared task to predict semantic similarity.
result 9 teams participated in the task, results made publicly available.
Paper proposes a neural network for generating better questions from text.
problem Automatic generation of relevant questions from sentences and paragraphs.
method Adaptive copying recurrent neural network model with a copying mechanism added to a bidirectional LSTM architecture.
result The model outperforms state-of-the-art methods in question generation metrics.
Paper tackles Arabic question similarity, outperforming state-of-the-art.
problem Detecting semantically similar questions in Arabic is challenging.
method Utilizes contextualized word representations (ELMo embeddings) trained on MSA and dialectic sentences, combined with a pairwise similarity layer.
result Achieves 93% F1-score on Modern Standard Arabic benchmark and 82% on dialectical benchmark.
Online surveys have the potential to support adaptive questions, where later questions depend on earlier responses. Past work has taken a rule-based approach, uniformly across all respondents. We envision a richer interpretation of adaptive questions, which we call dynamic question ordering (DQO), where question order …
R2DE assesses new exam questions quickly and accurately.
problem Assessing newly generated exam questions efficiently and accurately.
method R2DE uses NLP to estimate difficulty and discrimination of questions based on their text.
result R2DE can estimate question difficulty and discrimination quickly and accurately.
Unified QuesNet learns comprehensive representations for diverse test questions.
problem Lack of labeled data for test questions in online learning systems.
method Unified framework and two-level hierarchical pre-training algorithm for unsupervised learning of heterogeneous question representations.
result QuesNet effectively learns comprehensive question representations and outperforms existing methods.
James's octonionic Stiefel spaces questions answered partially.
problem Two fundamental questions about octonionic Stiefel spaces.
method Partial answers to James's questions about octonionic Stiefel spaces.
result Partial answers to James's questions about octonionic Stiefel spaces.
AI tested on 10 math questions from research.
problem Assessing AI's ability to solve research-level math problems.
method Shared 10 math questions not previously publicly available.
result Answers to questions are known to authors but encrypted.
Predicts student performance in interactive online question pools using GNNs.
problem Predicting student performance in interactive online question pools with evolving knowledge.
method Proposes R^2GCN, a GNN model for heterogeneous networks to predict student performance.
result Achieves higher accuracy in student performance prediction than traditional methods.
DiffQue estimates relative difficulty of questions in CQA services.
problem Estimating relative difficulty of questions in community Q&A services.
method Network-aided edge directionality prediction.
result DiffQue outperforms state-of-the-art methods by significant margins.
EduQG generates better educational questions by pre-training on scientific text.
problem Improving the quality of educational questions for scalable self-assessment.
method Adapting a large language model for educational question generation, pre-trained on scientific text.
result EduQG produces superior educational questions compared to baseline models.
Solved a specific case of Salter's question on Burau representation.
problem Under what conditions are matrices in the image of the Burau representation of B3. method Algorithmically constructed a counterexample to Salter's specific question.
result The central quotient of the Burau image group is not the central quotient of a certain subgroup of the unitary group.
This study analyzes financial equity research reports to identify frequently asked questions and automates 80% of them.
problem Insufficient empirical analysis of questions answered in financial equity research reports.
method Analyzed 72 financial equity research reports, classifying sentences into 169 unique question archetypes. Used public corporate reports to classify questions' potential for automation.
result Approximately 80% of financial equity research reports can be automated, with 78.7% of questions automatable.
We are raising questions on discrete and dense subgroups of Diff(I). Most of the questions are around the problems discussed in [A1]-[A4].
Abstract reviews known and open questions on spaces with lower Ricci bounds.
problem Understanding the structure and regularity of spaces with lower Ricci curvature bounds.
method Review of known results and presentation of open questions.
result Presentation of new open questions in the field.
Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for mo…
Paper proposes a fair grading method for randomized exams.
problem Ensuring fairness in grading for randomized exams.
method Maximum-likelihood estimator for Bradley-Terry-Luce model on student-question graph.
result Maximum-likelihood estimator is consistent and outperforms simple averaging in fairness and accuracy.
Stack Overflow is the most popular Q&A website among software developers. As a platform for knowledge sharing and acquisition, the questions posted in Stack Overflow usually contain a code snippet. Stack Overflow relies on users to properly tag the programming language of a question and it simply assumes that the progr…
Community-based Question Answering (CQA) sites play an important role in addressing health information needs. However, a significant number of posted questions remain unanswered. Automatically answering the posted questions can provide a useful source of information for online health communities. In this study, we deve…
Paper answers Gromov's compactness question on noncompact manifolds.
problem Gromov's compactness question on positive scalar curvature metrics.
method Construct examples and prove vanishing of certain index theoretic invariants.
result Positive answer for a class of 1-tame manifolds.
We study how to leverage off-the-shelf visual and linguistic data to cope with out-of-vocabulary answers in visual question answering task. Existing large-scale visual datasets with annotations such as image class labels, bounding boxes and region descriptions are good sources for learning rich and diverse visual conce…
Paper proposes a reinforcement learning framework for distant supervision of question parsing.
problem Lack of gold annotations for parsing in QA datasets.
method Reinforcement learning framework based on formal queries to learn mentions of entities and relations.
result Significant improvement in entity and relation linking compared to state of the art.
qDKT improves KT models by considering individual question outcomes.
problem Ignoring question-specific outcomes leads to inaccurate learner skill tracking.
method qDKT incorporates graph Laplacian regularization and uses a fastText-inspired initialization scheme.
result qDKT achieves state-of-the-art performance in predicting learner outcomes.
The paper tackles adaptive questioning to classify candidate ability.
problem Designing an optimal sequence of adaptive questions to classify candidate ability.
method Develops lower bounds and geometrical insights for sequential questioning strategies, and arrives at algorithms that match these bounds.
result Asymptotically, any candidate needs to be asked questions at most at two levels, facilitating endogenous exploration.
New model improves diversity in question generation over text.
problem Inadequate evaluation metrics for diverse questions.
method Proposed a variational encoder-decoder model and evaluation scheme.
result Improved diversity in generated questions without loss of quality.
QAInfomax improves reading comprehension by maximizing mutual information, achieving state-of-the-art performance.
problem Distractor sentences in question answering datasets are hard to distinguish from relevant ones.
method QAInfomax regularizes reading comprehension models to learn mutual information among passages, questions, and answers.
result QAInfomax achieves state-of-the-art performance on Adversarial-SQuAD dataset.
A new model answers questions about medical images.
problem Lack of transparency in deep learning models for medical imaging.
method A question-centric model that queries image models directly.
result The model achieves equal or higher accuracy than existing methods.
Enhanced ontology learning from text improves question-answering systems.
problem Improving ontology learning from unstructured text for better question-answering systems.
method Heuristically modified FP-Tree with DFA for concept extraction and frequent pattern mining for ontology learning.
result Our approach significantly improves question-answering system performance, answering 80% of questions compared to 28.4% with Text2Onto.
Enhanced QANet tackles unanswerable questions in MRC.
problem Improving performance on unanswerable questions in MRC.
method Extends QANet architecture to handle unanswerable questions through multi-task learning.
result EQuANt achieves close to 2x better performance on SQuAD 2 compared to baseline.
Quriosity analyzes curiosity-driven questions from diverse sources.
problem Understanding and analyzing human curiosity-driven questions.
method Collection of 13.5K questions from various sources, development of an iterative prompt improvement framework.
result 42% of questions are causal, revealing unique linguistic properties.
AdvReg improves VQA models but introduces instability and bias issues.
problem VQA models over-rely on linguistic biases, ignoring visual context.
method Adversarial regularization to encourage bias-free question representations.
result AdvReg yields side-effects like unstable gradients and reduced performance on in-domain examples.
We provide justifications for two questions on special maps on subgroups of the reals. We will show that the questions can be treated from different points of view. We also discuss two versions of Anderson's Involution Conjecture.
MAC Net is a compositional attention network designed for Visual Question Answering. We propose a modified MAC net architecture for Natural Language Question Answering. Question Answering typically requires Language Understanding and multi-step Reasoning. MAC net's unique architecture - the separation between memory an…
Discrete groups act properly on 3-space, solving Milnor's question.
problem Proper actions of discrete groups on 3-space.
method Historical review and recent progress.
result Existence of proper affine actions of free groups on 3-space.
GPT-4 assesses its confidence in answering USMLE questions with and without feedback.
problem Understanding AI's performance in healthcare applications, especially in sensitive areas like medical education.
method Used a prompting technique to evaluate GPT-4's confidence scores before and after answering USMLE questions, categorized into with and without feedback.
result Feedback influences relative confidence but doesn't consistently increase or decrease it.
We build a deep reinforcement learning (RL) agent that can predict the likelihood of an individual testing positive for malaria by asking questions about their household. The RL agent learns to determine which survey question to ask next and when to stop to make a prediction about their likelihood of malaria based on t…
Surveying 33 mapping questions posed by Heinonen and Semmes.
problem Mapping questions posed by Heinonen and Semmes.
method Survey and review of existing research.
result Current status of 33 mapping questions.
Survey on open manifolds with nonnegative Ricci curvature and open questions.
problem Understanding fundamental groups of open manifolds with nonnegative Ricci curvature.
method Survey and open questions.
result Discussion of open questions in the field.
Unified framework for simple question answering using subgraph ranking and joint-scoring.
problem Simple question answering with knowledge graphs is challenging.
method Unified framework focusing on subgraph selection and fact selection, with novel ranking and joint-scoring methods.
result Achieved state-of-the-art accuracy of 85.44% on SimpleQuestions dataset.
The paper teaches machines to ask clarifying questions by applying NLI.
problem Teaching machines to ask clarifying questions for better comprehension.
method The approach is to use NLI to determine if a clarification question is about a missing piece of information in a post.
result The best model improved precision@1 by 40% and 60% over state-of-the-art baselines.
Competency questions help experts select best clustering for energy data.
problem Ad hoc and subjective selection of clustering structures by domain experts.
method Formalize expert knowledge and requirements with competency questions.
result Competency questions improve reproducibility and evaluation of clustering applications.