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Found 21 papers, 4 papers with code
Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use
Our framework leverages recent advances in foundation models, both large language models and vision-language models, to carve out the concept space through conversation and by automatically labeling training data points.
Non-cascaded Control Barrier Functions for the Safe Control of Quadrotors
Researchers have developed various cascaded controllers and non-cascaded controllers for the navigation and control of quadrotors in recent years.
Safe Reinforcement Learning for a Robot Being Pursued but with Objectives Covering More Than Capture-avoidance
Reinforcement Learning (RL) algorithms show amazing performance in recent years, but placing RL in real-world applications such as self-driven vehicles may suffer safety problems.
Enhancing Sequential Recommendation with Graph Contrastive Learning
Specifically, GCL4SR employs a Weighted Item Transition Graph (WITG), built based on interaction sequences of all users, to provide global context information for each interaction and weaken the noise information in the sequence data.
JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu
In this work, we present JIZHI - a Model-as-a-Service system - that per second handles hundreds of millions of online inference requests to huge deep models with more than trillions of sparse parameters, for over twenty real-time recommendation services at Baidu, Inc.
A Dynamics Perspective of Pursuit-Evasion Games of Intelligent Agents with the Ability to Learn
It is shown that, in a pursuit-evasion game with a dynamics formulation, an evader is not able to escape from a slightly faster pursuer with an effective learned pursuit strategy, based on agile maneuvers and an effective learned evasion strategy.
DGL-KE: Training Knowledge Graph Embeddings at Scale
Experiments on knowledge graphs consisting of over 86M nodes and 338M edges show that DGL-KE can compute embeddings in 100 minutes on an EC2 instance with 8 GPUs and 30 minutes on an EC2 cluster with 4 machines with 48 cores/machine.
Distributed, Parallel, and Cluster Computing
Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding
Speech-to-text translation (ST), which translates source language speech into target language text, has attracted intensive attention in recent years.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Multi-agent Learning for Neural Machine Translation
Conventional Neural Machine Translation (NMT) models benefit from the training with an additional agent, e. g., dual learning, and bidirectional decoding with one agent decoding from left to right and the other decoding in the opposite direction.
Baidu Neural Machine Translation Systems for WMT19
In this paper we introduce the systems Baidu submitted for the WMT19 shared task on Chinese{\textless}-{\textgreater}English news translation.
DuTongChuan: Context-aware Translation Model for Simultaneous Interpreting
In this paper, we present DuTongChuan, a novel context-aware translation model for simultaneous interpreting.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
End-to-End Speech Translation with Knowledge Distillation
End-to-end speech translation (ST), which directly translates from source language speech into target language text, has attracted intensive attentions in recent years.
Multiple Sclerosis Lesion Inpainting Using Non-Local Partial Convolutions
However, existing methods inpaint lesions based on texture information derived from local surrounding tissue, often leading to inconsistent inpainting and the generation of artifacts such as intensity discrepancy and blurriness.
Modeling Coherence for Discourse Neural Machine Translation
Discourse coherence plays an important role in the translation of one text.
STACL: Simultaneous Translation with Implicit Anticipation and Controllable Latency using Prefix-to-Prefix Framework
Simultaneous translation, which translates sentences before they are finished, is useful in many scenarios but is notoriously difficult due to word-order differences.
Robust Neural Machine Translation with Joint Textual and Phonetic Embedding
Neural machine translation (NMT) is notoriously sensitive to noises, but noises are almost inevitable in practice.
Multi-channel Encoder for Neural Machine Translation
This design of encoder yields relatively uniform composition on source sentence, despite the gating mechanism employed in encoding RNN.
