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08/01/2023
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models
Today, large language models (LLMs) are taught to use new tools by provi...
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05/03/2023
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Deploying large language models (LLMs) is challenging because they are m...
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03/06/2023
Multimodal Prompting with Missing Modalities for Visual Recognition
In this paper, we tackle two challenges in multimodal learning for visua...
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02/06/2023
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval
In Composed Image Retrieval (CIR), a user combines a query image with te...
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06/02/2022
Prefix Conditioning Unifies Language and Label Supervision
Vision-language contrastive learning suggests a new learning paradigm by...
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03/16/2022
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction
Sequence modeling has demonstrated state-of-the-art performance on natur...
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01/10/2022
Towards Group Robustness in the presence of Partial Group Labels
Learning invariant representations is an important requirement when trai...
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12/21/2021
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types
We introduce anomaly clustering, whose goal is to group data into semant...
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06/21/2021
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
Natural reading orders of words are crucial for information extraction f...
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06/11/2021
Self-Trained One-class Classification for Unsupervised Anomaly Detection
Anomaly detection (AD), separating anomalies from normal data, has vario...
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01/11/2021
Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts
Learning visual knowledge from massive weakly-labeled web videos has att...
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06/02/2020
Learning to Branch for Multi-Task Learning
Training multiple tasks jointly in one deep network yields reduced laten...
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05/10/2020
A Simple Semi-Supervised Learning Framework for Object Detection
Semi-supervised learning (SSL) has promising potential for improving the...
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03/10/2019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
In this work, we connect two distinct concepts for unsupervised domain a...
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11/07/2017
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Deep multitask networks, in which one neural network produces multiple p...
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03/18/2017
RoomNet: End-to-End Room Layout Estimation
This paper focuses on the task of room layout estimation from a monocula...
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03/09/2016
Recursive Recurrent Nets with Attention Modeling for OCR in the Wild
We present recursive recurrent neural networks with attention modeling (...
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09/30/2015
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
We seek to improve deep neural networks by generalizing the pooling oper...
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05/11/2015
Training Deeper Convolutional Networks with Deep Supervision
One of the most promising ways of improving the performance of deep conv...
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09/18/2014