公开(公告)号：US11416747B2

公开(公告)日：2022-08-16

申请号：US16355290

申请日：2019-03-15

Applicant: salesforce.com, inc.

Inventor： Richard Socher ,  Caiming Xiong ,  Kai Sheng Tai

IPC: G06N3/08 ,  G06N3/04 ,  G06T7/00 ,  G06K9/62 ,  G06F30/00 ,  G06V10/96 ,  G06V10/44 ,  G06V20/64

Abstract: A method of classifying three-dimensional (3D) data includes receiving three-dimensional (3D) data and processing the 3D data using a neural network that includes a plurality of subnetworks arranged in a sequence and the data is processed through each of the subnetworks. Each of the subnetworks is configured to receive an output generated by a preceding subnetwork in the sequence, process the output through a plurality of parallel 3D convolution layer paths of varying convolution volume, process the output through a parallel pooling path, and concatenate output of the 3D convolution layer paths and the pooling path to generate an output representation from each of the subnetworks. Following processing the data through the subnetworks, the method includes processing the output of a last one of the subnetworks in the sequence through a vertical pooling layer to generate an output and classifying the received 3D data based upon the generated output.

公开(公告)号：US20220103491A1

公开(公告)日：2022-03-31

申请号：US17037554

申请日：2020-09-29

Applicant: salesforce.com, inc.

Inventor： Xinyi Yang ,  Tian Xie ,  Caiming Xiong ,  Wenhao Liu ,  Huan Wang ,  Kazuma Hashimoto ,  Jin Qu ,  Feihong Wu ,  Yingbo Zhou

IPC: H04L12/58 ,  G06N3/04 ,  G06K9/62 ,  G06F40/35

Abstract: A conversation engine performs conversations with users using chatbots customized for performing a set of tasks that can be performed using an online system. The conversation engine loads a chatbot configuration that specifies the behavior of a chatbot including the tasks that can be performed by the chatbot, the types of entities relevant to each task, and so on. The conversation may be voice based and use natural language. The conversation engine may load different chatbot configurations to implement different chatbots. The conversation engine receives a conversation engine configuration that specifies the behavior of the conversation engine across chatbots. The system may be a multi-tenant system that allows customization of the chatbots for each tenant.

公开(公告)号：US11281863B2

公开(公告)日：2022-03-22

申请号：US16518905

申请日：2019-07-22

Applicant: salesforce.com, inc.

Inventor： Nitish Shirish Keskar ,  Bryan McCann ,  Richard Socher ,  Caiming Xiong

IPC: G06F16/332 ,  G06F40/30 ,  G06F40/284 ,  G06N3/08

Abstract: Systems and methods for unifying question answering and text classification via span extraction include a preprocessor for preparing a source text and an auxiliary text based on a task type of a natural language processing task, an encoder for receiving the source text and the auxiliary text from the preprocessor and generating an encoded representation of a combination of the source text and the auxiliary text, and a span-extractive decoder for receiving the encoded representation and identifying a span of text within the source text that is a result of the NLP task. The task type is one of entailment, classification, or regression. In some embodiments, the source text includes one or more of text received as input when the task type is entailment, a list of classifications when the task type is entailment or classification, or a list of similarity options when the task type is regression.

公开(公告)号：US20220058348A1

公开(公告)日：2022-02-24

申请号：US17124317

申请日：2020-12-16

Applicant: salesforce.com, inc.

Inventor： Tianxing He ,  Ehsan Hosseini-Asl ,  Bryan McCann ,  Caiming Xiong

IPC: G06F40/58

Abstract: Embodiments described herein provide natural language processing (NLP) systems and methods that utilize energy-based models (EBMs) to compute an exponentially-weighted energy-like term in the loss function to train an NLP classifier. Specifically, noise contrastive estimation (NCE) procedures are applied together with the EBM-based loss objectives for training the NLPs.

公开(公告)号：US11244111B2

公开(公告)日：2022-02-08

申请号：US16668333

申请日：2019-10-30

Applicant: salesforce.com, inc.

Inventor： Jiasen Lu ,  Caiming Xiong ,  Richard Socher

IPC: G06K9/00 ,  G06F40/274 ,  G06K9/62 ,  G06K9/46 ,  G06N3/04 ,  G06N3/08 ,  G06F40/30 ,  G06F40/169 ,  G06K9/48 ,  G06K9/66

Abstract: The technology disclosed presents a novel spatial attention model that uses current hidden state information of a decoder long short-term memory (LSTM) to guide attention and to extract spatial image features for use in image captioning. The technology disclosed also presents a novel adaptive attention model for image captioning that mixes visual information from a convolutional neural network (CNN) and linguistic information from an LSTM. At each timestep, the adaptive attention model automatically decides how heavily to rely on the image, as opposed to the linguistic model, to emit the next caption word. The technology disclosed further adds a new auxiliary sentinel gate to an LSTM architecture and produces a sentinel LSTM (Sn-LSTM). The sentinel gate produces a visual sentinel at each timestep, which is an additional representation, derived from the LSTM's memory, of long and short term visual and linguistic information.

公开(公告)号：US20210389736A1

公开(公告)日：2021-12-16

申请号：US17460691

申请日：2021-08-30

Applicant: salesforce.com, inc.

Inventor： Ehsan Hosseini-Asl ,  Caiming Xiong ,  Yingbo Zhou ,  Richard Socher

IPC: G05B13/02 ,  G10L21/003 ,  G06N3/02

Abstract: A method for training parameters of a first domain adaptation model. The method includes evaluating a cycle consistency objective using a first task specific model associated with a first domain and a second task specific model associated with a second domain, and evaluating one or more first discriminator models to generate a first discriminator objective using the second task specific model. The one or more first discriminator models include a plurality of discriminators corresponding to a plurality of bands that corresponds domain variable ranges of the first and second domains respectively. The method further includes updating, based on the cycle consistency objective and the first discriminator objective, one or more parameters of the first domain adaptation model for adapting representations from the first domain to the second domain.

公开(公告)号：US20210383212A1

公开(公告)日：2021-12-09

申请号：US17105262

申请日：2020-11-25

Applicant: salesforce.com, inc.

Inventor： Govardana Sachithanandam Ramachandran ,  Kazuma Hashimoto ,  Caiming Xiong ,  Richard Socher

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/00 ,  G06F40/35

Abstract: Embodiments described herein provide safe policy improvement (SPI) in a batch reinforcement learning framework for a task-oriented dialogue. Specifically, a batch reinforcement learning framework for dialogue policy learning is provided, which improves the performance of the dialogue and learns to shape a reward that reasons the invention behind human response rather than just imitating the human demonstration.

公开(公告)号：US20210374603A1

公开(公告)日：2021-12-02

申请号：US17010465

申请日：2020-09-02

Applicant: salesforce.com, Inc.

Inventor： Congying Xia ,  Caiming Xiong

IPC: G06N20/00 ,  G06F40/30 ,  G06F40/284

Abstract: Embodiments described herein provide a composed variational natural language generation (CLANG) model that is configured to generate training samples for few-shot intents. Specifically, the CLANG model may build connections between existing training samples of many-shot intents and new training samples of few-shot intents by modeling an intent as a combination of a domain and an action. In this way, the CLANG model transfers knowledge from existing many-shot intents to few-shot intents in natural language generation by learning how to compose utterances with many-shot intents and transferring such knowledge to few-shot intents.

公开(公告)号：US20210279551A1

公开(公告)日：2021-09-09

申请号：US17331337

申请日：2021-05-26

Applicant: salesforce.com, inc.

Inventor： Kazuma Hashimoto ,  Caiming Xiong ,  Richard Socher

IPC: G06N3/04 ,  G06N3/08 ,  G06F40/30 ,  G06F40/205 ,  G06F40/216 ,  G06F40/253 ,  G06F40/284 ,  G06N3/063

Abstract: The technology disclosed provides a so-called “joint many-task neural network model” to solve a variety of increasingly complex natural language processing (NLP) tasks using growing depth of layers in a single end-to-end model. The model is successively trained by considering linguistic hierarchies, directly connecting word representations to all model layers, explicitly using predictions in lower tasks, and applying a so-called “successive regularization” technique to prevent catastrophic forgetting. Three examples of lower level model layers are part-of-speech (POS) tagging layer, chunking layer, and dependency parsing layer. Two examples of higher level model layers are semantic relatedness layer and textual entailment layer. The model achieves the state-of-the-art results on chunking, dependency parsing, semantic relatedness and textual entailment.

公开(公告)号：US11087092B2

公开(公告)日：2021-08-10

申请号：US16399871

申请日：2019-04-30

Applicant: salesforce.com, inc.

Inventor： Stephan Zheng ,  Wojciech Kryscinski ,  Michael Shum ,  Richard Socher ,  Caiming Xiong

IPC: G06F40/30 ,  G06N3/08 ,  G06F40/205

Abstract: Approaches for determining a response for an agent in an undirected dialogue are provided. The approaches include a dialogue generating framework comprising an encoder neural network, a decoder neural network, and a language model neural network. The dialogue generating framework generates a sketch sentence response with at least one slot. The sketch sentence response is generated word by word and takes into account the undirected dialogue and agent traits of the agent making the response. The dialogue generating framework generates sentence responses by filling the slot with words from the agent traits. The dialogue generating framework ranks the sentence responses according to perplexity by passing the sentence responses through a language model and selects a final response which is a sentence response that has a lowest perplexity.