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Found 49 papers, 12 papers with code
Alibaba’s Submission for the WMT 2020 APE Shared Task: Improving Automatic Post-Editing with Pre-trained Conditional Cross-Lingual BERT
We also apply an imitation learning strategy to augment a reasonable amount of pseudo APE training data, potentially preventing the model to overfit on the limited real training data and boosting the performance on held-out data.
QEMind: Alibaba’s Submission to the WMT21 Quality Estimation Shared Task
Quality Estimation, as a crucial step of quality control for machine translation, has been explored for years.
HTML: A Parametric Hand Texture Model for 3D Hand Reconstruction and Personalization
3D hand reconstruction from images is a widely-studied problem in computer vision and graphics, and has a particularly high relevance for virtual and augmented reality.
OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations
With the rise of deep learning, facial recognition technology has seen extensive research and rapid development.
Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion
Multimodal medical image fusion is a crucial task that combines complementary information from different imaging modalities into a unified representation, thereby enhancing diagnostic accuracy and treatment planning.
Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language
English, as a very high-resource language, enables the pretraining of high-quality large language models (LLMs).
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
In particular, for many FL algorithms, the convergence rate grows dramatically when the number of local updates becomes large, especially when the product of the gradient divergence and local Lipschitz constant is large.
Label-free Neural Semantic Image Synthesis
Neural layouts are advantageous as they provide rich descriptions of the desired image, containing both semantics and detailed geometry of the scene.
ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World
Existing clinical diagnostic evaluation benchmarks for evaluating medical agents powered by LLMs have severe limitations.
Truncated Variance Reduced Value Iteration
We provide an $\tilde{O}(A_{\text{tot}}[(1 - \gamma)^{-3}\epsilon^{-2} + (1 - \gamma)^{-2}])$-time algorithm in the sampling setting, where the probability transition matrix is unknown but accessible through a generative model which can be queried in $\tilde{O}(1)$-time, and an $\tilde{O}(s + (1-\gamma)^{-2})$-time algorithm in the offline setting where the probability transition matrix is known and $s$-sparse.
UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter Tuning
Semantic analysis on visible (RGB) and infrared (IR) images has gained attention for its ability to be more accurate and robust under low-illumination and complex weather conditions.
ODFormer: Semantic Fundus Image Segmentation Using Transformer for Optic Nerve Head Detection
However, the significant discrepancy between fundus image datasets, each generated using a single type of fundus camera, poses challenges to the generalizability of ONH detection approaches developed based on semantic segmentation networks.
Ten simple rules for collaborating with wet lab researchers for computational researchers
Computational biologists are frequently engaged in collaborative data analysis with wet lab researchers.
DNABERT-S: Pioneering Species Differentiation with Species-Aware DNA Embeddings
We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space.
MPRE: Multi-perspective Patient Representation Extractor for Disease Prediction
Patient representation learning based on electronic health records (EHR) is a critical task for disease prediction.
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera
3D hand tracking from a monocular video is a very challenging problem due to hand interactions, occlusions, left-right hand ambiguity, and fast motion.
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation with human judgments.
Strings from the Library of Babel: Random Sampling as a Strong Baseline for Prompt Optimisation
Recent prompt optimisation approaches use the generative nature of language models to produce prompts -- even rivaling the performance of human-curated prompts.
Synslator: An Interactive Machine Translation Tool with Online Learning
Interactive machine translation (IMT) has emerged as a progression of the computer-aided translation paradigm, where the machine translation system and the human translator collaborate to produce high-quality translations.
Non-parametric, Nearest-neighbor-assisted Fine-tuning for Neural Machine Translation
We explore whether such non-parametric models can improve machine translation models at the fine-tuning stage by incorporating statistics from the kNN predictions to inform the gradient updates for a baseline translation model.
ADELT: Transpilation Between Deep Learning Frameworks
We propose the Adversarial DEep Learning Transpiler (ADELT), a novel approach to source-to-source transpilation between deep learning frameworks.
Cost-aware Defense for Parallel Server Systems against Reliability and Security Failures
Parallel server systems in transportation, manufacturing, and computing heavily rely on dynamic routing using connected cyber components for computation and communication.
TSMind: Alibaba and Soochow University's Submission to the WMT22 Translation Suggestion Task
The leader board finally shows that our submissions are ranked first in three of four language directions in the Naive TS task of the WMT22 Translation Suggestion task.
Easy Guided Decoding in Providing Suggestions for Interactive Machine Translation
Human translators perform post editing on machine translations to correct errors in the scene of computer aided translation.
HandFlow: Quantifying View-Dependent 3D Ambiguity in Two-Hand Reconstruction with Normalizing Flow
Through this, we demonstrate the quality of our probabilistic reconstruction and show that explicit ambiguity modeling is better-suited for this challenging problem.
Blessing from Human-AI Interaction: Super Reinforcement Learning in Confounded Environments
This approach utilizes the observed action, either from AI or humans, as input for achieving a stronger oracle in policy learning for the decision maker (humans or AI).
Rethinking Textual Adversarial Defense for Pre-trained Language Models
However, we find that most existing textual adversarial examples are unnatural, which can be easily distinguished by both human and machine.
Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation
The comprehensive experiments on three fine-grained benchmark datasets for two few-shot tasks verify that FicNet has excellent performance compared to the state-of-the-art methods.
Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity
Due to the high human cost of annotation, it is non-trivial to curate a large-scale medical dataset that is fully labeled for all classes of interest.
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
We question the validity of current evaluation of robustness of PrLMs based on these non-natural adversarial samples and propose an anomaly detector to evaluate the robustness of PrLMs with more natural adversarial samples.
QEMind: Alibaba's Submission to the WMT21 Quality Estimation Shared Task
Quality Estimation, as a crucial step of quality control for machine translation, has been explored for years.
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation
Quality Estimation (QE) plays an essential role in applications of Machine Translation (MT).
Projected State-action Balancing Weights for Offline Reinforcement Learning
Offline policy evaluation (OPE) is considered a fundamental and challenging problem in reinforcement learning (RL).
RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video
Moreover, we demonstrate that our approach offers previously unseen two-hand tracking performance from RGB, and quantitatively and qualitatively outperforms existing RGB-based methods that were not explicitly designed for two-hand interactions.
Matrix Completion with Model-free Weighting
In particular, the proposed method achieves a stronger guarantee than existing work in terms of the scaling with respect to the observation probabilities, under asymptotically heterogeneous missing settings (where entry-wise observation probabilities can be of different orders).
Defending Pre-trained Language Models from Adversarial Word Substitutions Without Performance Sacrifice
In detail, we design an auxiliary anomaly detection classifier and adopt a multi-task learning procedure, by which PrLMs are able to distinguish adversarial input samples.
Enhancing Pre-trained Language Model with Lexical Simplification
By substituting complex words with simple alternatives, lexical simplification (LS) is a recognized method to reduce such lexical diversity, and therefore to improve the understandability of sentences.
EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream
Due to the different data modality of event cameras compared to classical cameras, existing methods cannot be directly applied to and re-trained for event streams.
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
Furthermore, we extend our analytical approach based on "upward" and "downward" divergences to study the convergence for the general case of H-SGD with more than two levels, where the "sandwich behavior" still holds.
Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing
With the advent of neural machine translation, there has been a marked shift towards leveraging and consuming the machine translation results.
Generative Model-Based Loss to the Rescue: A Method to Overcome Annotation Errors for Depth-Based Hand Pose Estimation
We propose to use a model-based generative loss for training hand pose estimators on depth images based on a volumetric hand model.
Convex Optimisation for Inverse Kinematics
We consider the problem of inverse kinematics (IK), where one wants to find the parameters of a given kinematic skeleton that best explain a set of observed 3D joint locations.
Neural Zero-Inflated Quality Estimation Model For Automatic Speech Recognition System
The performances of automatic speech recognition (ASR) systems are usually evaluated by the metric word error rate (WER) when the manually transcribed data are provided, which are, however, expensively available in the real scenario.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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An encoding framework with brain inner state for natural image identification
The framework comprises two parts: forward encoding model that deals with visual stimuli and inner state model that captures influence from intrinsic connections in the brain.
Predicting Eating Events in Free Living Individuals -- A Technical Report
For predicting food purchasing events, the RBF-SVM model (0. 7395) outperforms others.
Low-Rank Phase Retrieval via Variational Bayesian Learning
We propose a hierarchical prior model for low-rank phase retrieval, in which a Gaussian-Wishart hierarchical prior is placed on the underlying low-rank matrix to promote the low-rankness of the matrix.
Alibaba Submission for WMT18 Quality Estimation Task
The goal of WMT 2018 Shared Task on Translation Quality Estimation is to investigate automatic methods for estimating the quality of machine translation results without reference translations.
"Bilingual Expert" Can Find Translation Errors
Recent advances in statistical machine translation via the adoption of neural sequence-to-sequence models empower the end-to-end system to achieve state-of-the-art in many WMT benchmarks.
