Study finds neural dialog models struggle with conversational tasks.
problem Insufficient understanding of dialog by neural models.
method Analysis of internal representations and evaluation of model performance.
result Neural dialog models lack key conversational skills like answering questions and inferring contradiction.
HRL improves open-domain dialog models by optimizing long-term conversational goals.
problem Challenges in open-domain dialog generation, including repetitive outputs, difficulty tracking conversational goals, and inappropriate text.
method Proposes VHRL, a hierarchical reinforcement learning approach using policy gradients to tune utterance-level embeddings of a variational sequence model.
result Significant improvements in human evaluation and automatic metrics over state-of-the-art dialog models.
Meena is a chatbot trained on social media data, achieving human-like conversation quality.
problem Creating a chatbot that can have human-like conversations in an open-domain setting.
method End-to-end training of a 2.6B parameter neural network on social media data, using perplexity and a human evaluation metric (SSA) to assess quality.
result Meena achieves a high human-like conversation quality (79% SSA) when compared to existing chatbots.
Paper proposes a self-play method to approximate human evaluation of conversational agents.
problem Challenges in evaluating open-domain dialog systems.
method Self-play scenario with sentiment and semantic coherence proxies.
result Self-play metric correlates significantly with human ratings (r>.7, p<.05).
MILABOT is a chatbot trained to converse with humans using deep reinforcement learning.
problem Developing a conversational agent capable of handling open-domain small talk topics.
method Deep reinforcement learning applied to crowdsourced and real-world data.
result MILABOT outperformed other systems in A/B testing with real-world users.
Paper improves emotion expression in AI chatbots.
problem AI chatbots generate responses that lack emotion.
method Developed neural models to express specific emotions in generated responses.
result An encoder-decoder model with multiple attention layers performs best in expressing required emotion.
Study combines chit-chat and goal-oriented dialogue in fantasy games.
problem Combining naturalistic chit-chat with goal-oriented tasks in fantasy games.
method Trained a goal-oriented model with reinforcement learning against an imitation-learned chit-chat model using two approaches.
result Both models outperform a baseline and can converse naturally to achieve goals.
Novel RL algorithms learn from human interaction data without exploration.
problem Efficiently learning from off-policy data in reinforcement learning.
method Developed off-policy batch RL algorithms using KL-control and dropout-based uncertainty.
result Successfully learned multiple reward functions from human interaction data.
This study compares hierarchical and non-hierarchical models for open-domain multi-turn dialog generation.
problem Which kind of models (hierarchical or non-hierarchical) is better for open-domain multi-turn dialog generation?
method Systematically compared nearly all representative hierarchical and non-hierarchical models over the same experimental settings.
result Nearly all hierarchical models are worse than non-hierarchical models in open-domain multi-turn dialog generation, except for HRAN.
In this Note we establish a relation between sections in globally generated holomorphic vector bundles on Kähler manifolds, isotropic with respect to a non-degenerate quadratic form, and totally geodesic foliations on Euclidean open domains. We find a geometric condition for a totally geodesic foliation to originate in…
Improved representations from multiple video views.
problem Learning reliable representations across unaligned video modalities.
method Correlation-based representation learning on a 4-way parallel multimodal dataset.
result Best models achieve retrieval rates up to 96.9% on open-domain instructional videos.
New domains of discontinuity found for Anosov representations.
problem Understanding Anosov representations acting on homogeneous spaces.
method Constructing open domains of discontinuity for Anosov representations acting on specific homogeneous spaces.
result Describes the largest possible open domains of discontinuity for Zariski dense Anosov representations.
We investigate different concentration-compactness phenomena related to the Q-curvature in arbitrary even dimension. We first treat the case of an open domain in R2m, then that of a closed manifold and, finally, the particular case of the sphere S2m. In all cases we allow the sign of the Q-curvature to vary, …
We construct open domains in Euclidean 3-space which do not admit complete properly immersed minimal surfaces with an annular end. These domains can not be smooth by a recent result of Martin and Morales
Paper develops a model for verifying facts in tables without pre-retrieved evidence.
problem Verification of factual claims in structured data, especially in open-domain settings.
method Joint reranking-and-verification model that fuses evidence documents.
result Model achieves comparable performance to closed-domain state-of-the-art on TabFact dataset.
It is a theorem of S. Bando that if g(t) is a solution to the Ricci flow on a compact manifold M, then (M,g(t)) is real-analytic for each t>0. In this note, we extend his result to smooth solutions on open domains U⊂M.
We prove that given an open Riemann surface N, there exists an open domain M⊂N homeomorphic to N which properly holomorphically embeds in C2. Furthermore, M can be chosen with hyperbolic conformal type. In particular, any open orientable surface admits a complex structure properly holomorphic…
Improved text embeddings enhance retrieval from a knowledge base.
problem Efficiently retrieving relevant paragraphs from a large knowledge base.
method Used Stanford Question Answering Dataset (SQuAD) for open-domain question answering. Compared various text-embedding methods and trained deep residual neural models for retrieval.
result Training deep residual neural models for retrieval purposes significantly improves paragraph recall.
The reduction of biharmonic maps equation in terms of the Maurer-Cartan form for all smooth map of any compact Riemannian manifolds into a compact Lie group with bi-invariant Riemannian metric is obtained. By this formula, all the biharmonic curves into a compact Lie group and all biharmonic maps from a 2-dimensional o…
Consider a strictly convex bounded regular domain C of R3. For any arbitrary finite topological type we find a compact Riemann surface M, an open domain M⊂M with the fixed topological type, and a conformal complete proper minimal immersion X:M→C which can be extended to a conti…
In this paper, the description of biharmonic map equation in terms of the Maurer-Cartan form for all smooth map of a compact Riemannian manifold into a Riemannian symmetric space (G/K,h) induced from the bi-invariant Riemannian metric h on G is obtained. By this formula, all biharmonic curves into symmetric space…
In this paper we analyze the problem of the geodesic connectedness of subsets of Riemannian manifolds. By using variational methods, the geodesic connectedness of open domains (whose boundaries can be not differentiable and not convex) of a smooth Riemannian manifold is proved. In some cases also the convexity of the d…
We present a geometric proof of the averaging theorem for perturbed dynamical systems on a Riemannian manifold, in the case where the flow of the unperturbed vector field is periodic and the S1-action associated to this vector field is not necessarily trivial. We generalize the averaging procedure \cite{A…
Adapting the method of Andrews-Clutterbuck we prove an eigenvalue gap theorem for a class of non symmetric second order linear elliptic operators on a convex domain in euclidean space. The class of operators includes the Bakry-Emery laplacian with potential and any operator with second order term the laplacian whose fi…
End-to-end speech recognition system trained on GPUs and CPUs.
problem Building state-of-the-art speech recognition systems.
method Utilizes CPUs and GPUs for training, data augmentation, and neural network updates. Uses vocal tract length perturbation and acoustic simulator for data augmentation. Employed Horovod allreduce for training.
result Achieved 7.92% WER on proprietary English Bixby open domain test set using a Bidirectional Full Attention (BFA) model.
A family of probability distributions parametrized by an open domain Λ in Rn defines the Fisher information matrix on this domain which is positive semi-definite. In information geometry the standard assumption has been that the Fisher information matrix tensor is positive definite defining in this way a Riemannia…
We consider an open domain with a compact boundary in an Euclidean space and a Schroedinger operator with magnetic field on this domain. We give sufficient conditions on the rate of growth of the magnetic field near the boundary which guarantees essential self-adjointness of this operator. From the physical point of vi…
New mathematical surfaces without boundaries found.
problem Existence of nonlocal free boundary minimal surfaces.
method Fractional perimeter critical points with invariant boundary.
result Existence of nonlocal free boundary minimal surfaces without boundaries.
Paper improves conversion prediction models for online advertising.
problem Predicting different types of conversions in online advertising.
method Multi-Task Learning with MT-FwFM.
result Improved AUC by 0.74% and 0.84% on two conversion types, and overall AUC by 0.50%.
Study examines cash conversion cycle in manufacturing firms, finding negative relationships with profitability and size.
problem Understanding cash conversion cycle in manufacturing firms and its impact on profitability and size.
method Empirical study of 30 manufacturing firms in Dhaka Stock Exchanges, categorizing them into six industries, analyzing industry averages and relationships with size and profitability.
result Negative relationship between cash conversion cycle and profitability, especially ROE; negative relationship with firm size in terms of net sales.
Framework converts singer identity and vocal technique from non-parallel corpora.
problem Converts singer identity and vocal technique from non-parallel corpora.
method Uses variational autoencoders with separate encoders for singer identity and vocal technique.
result Successfully disentangles and converts singer identity and vocal technique.
FasterVoiceGrad speeds up VC by 6-7x with novel distillation.
problem Slow iterative sampling in diffusion-based VC models.
method Adversarial diffusion conversion distillation (ADCD) to create a faster one-step model.
result 6.6-6.9 and 1.8x faster on GPU and CPU, respectively.
Efficiently estimates conversion probability in online display advertising.
problem Estimating conversion probability with delays and large data sets.
method Compromise estimator combining logistic regression and joint model.
result Computational efficiency with less bias than previous methods.
Conversational UCB accelerates bandit learning with user feedback.
problem Slow learning speed in traditional contextual bandit algorithms.
method Generalized contextual bandit to conversational contextual bandit, leveraging both behavioral and conversational feedbacks.
result ConUCB achieves a smaller regret upper bound, indicating faster learning speed.
Lecture notes on BGG complexes using Lie groups and algebras.
problem Constructing BGG complexes on open domains.
method Representation theory of semisimple Lie groups and Lie algebras.
result Introduction of BGG complexes with Lie group and algebra insights.
In this paper we find, for any arbitrary finite topological type, a compact Riemann surface M, an open domain M⊂M with the fixed topological type, and a conformal complete minimal immersion X:M→R3 which can be extended to a continuous map X:Mˉ→R3, such that $X_{|\partial M…
Automated system extracts medication regimens from medical conversations.
problem Extract relevant medication information from medical conversations.
method QA task approach, combined QA and Information Extraction, data augmentation, public embeddings, pretraining.
result Improved accuracy in extracting dosage and frequency from 54.28 and 37.13 to 89.57 and 45.94.
DLGNet improves dialogue response generation by leveraging transformer architecture.
problem Lack of relevance, diversity, and coherence in dialogue responses.
method Transformer-based model for dialogue response generation, incorporating long-range structures and random paddings.
result Significant improvements over state-of-the-art models on multiple datasets.
Improved speech recognition for medical conversations.
problem Transcribing accurate doctor-patient conversations.
method Collected a large dataset, designed realistic tasks, explored alignment and model types (CTC and LAS).
result LAS models were more resilient to noisy data, while CTC required more data cleanup.
FedConPE improves conversational recommender systems efficiency and privacy.
problem Efficiently eliciting user preferences in interactive systems with heterogeneous clients.
method Phase elimination-based federated conversational bandit algorithm with adaptive key term construction.
result Minimizes uncertainty across all dimensions in feature space and offers improved efficiency and privacy.
Solution for voice conversion with limited data using hierarchical seq2seq and attention models.
problem Voice conversion between speakers with limited parallel audio pairs.
method Hierarchical sequence to sequence model with attention-based decoder, trained on single speaker dataset.
result Improved voice conversion quality using mel spectrograms and wavenet vocoder.
Proposes a multi-state model for evaluating life insurance conversion options.
problem Evaluating the value of conversion options in life insurance contracts.
method Age-indexed semi-Markov chains to model duration, time non-homogeneity, and ageing effects.
result Validates the model's ability to accurately evaluate conversion option values.
Study shows distance to boundary is always attained on varifolds with bounded curvature.
problem Understanding varifolds with bounded mean curvature in Riemannian manifolds.
method Proves a barrier principle at infinity using sharp maximum principles.
result Distance to boundary is always attained on varifolds with bounded curvature.
Study proposes a time-aware model to predict user conversion intent.
problem Weak predictive signals from users not suitable for conversion prediction.
method Time-aware approach to model user activities and capture conversion intent signals.
result Approach outperforms other models on real-world datasets.
Improved voice conversion with semi-supervised learning.
problem Voice conversion with limited parallel data.
method Amortized variational inference with parallel and non-parallel utterances.
result Semi-supervised training improves voice conversion performance.
Improved SAR in asynchronous conversations using neural models and unlabeled data.
problem Lack of labeled data for SAR in asynchronous conversations.
method Hierarchical LSTM-CRF model, semi-supervised learning with word embeddings, adversarial training.
result Adversarial training improves SAR performance by leveraging labeled data from synchronous domains.
CycleGAN-VC3 improves CycleGAN-VCs for mel-spectrogram conversion.
problem Ambiguity in CycleGAN-VC/VC2 effectiveness for mel-spectrogram conversion.
method Proposes CycleGAN-VC3 with time-frequency adaptive normalization (TFAN).
result CycleGAN-VC3 outperforms or matches CycleGAN-VC2 for mel-spectrogram conversion.
ConvS2S-VC converts voice characteristics and pitch contour using a fully convolutional seq2seq model.
problem Voice conversion with preservation of pitch contour and duration.
method Fully convolutional seq2seq architecture with conditional batch normalization.
result ConvS2S-VC outperforms baseline methods in sound quality and speaker similarity.