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09/17/2023
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles
Previous research in multi-document news summarization has typically con...
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08/11/2023
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
The massive successes of large language models (LLMs) encourage the emer...
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07/19/2023
DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI
Despite advancements in conversational AI, language models encounter cha...
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07/18/2023
REX: Rapid Exploration and eXploitation for AI Agents
In this paper, we propose an enhanced approach for Rapid Exploration and...
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02/18/2023
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
The Pretrained Foundation Models (PFMs) are regarded as the foundation f...
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01/06/2023
Model-Agnostic Hierarchical Attention for 3D Object Detection
Transformers as versatile network architectures have recently seen great...
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12/15/2022
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation
Human evaluation is the foundation upon which the evaluation of both sum...
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11/11/2022
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
State-of-the-art summarization models still struggle to be factually con...
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08/07/2022
Generating Negative Samples for Sequential Recommendation
To make Sequential Recommendation (SR) successful, recent works focus on...
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07/18/2022
Marvista: A Human-AI Collaborative Reading Tool
We present Marvista – a human-AI collaborative tool that employs a suite...
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05/31/2022
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation
Counterfactual explanation is an important Explainable AI technique to e...
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04/27/2022
Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework
Current contrastive learning frameworks focus on leveraging a single sup...
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01/28/2022
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Vision-Language Pre-training (VLP) has advanced the performance for many...
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11/18/2021
Towards Open Vocabulary Object Detection without Human-provided Bounding Boxes
Despite great progress in object detection, most existing methods are li...
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10/21/2021
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
In Domain Generalization (DG) settings, models trained on a given set of...
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09/20/2021
Merlion: A Machine Learning Library for Time Series
We introduce Merlion, an open-source machine learning library for time s...
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06/17/2021
DocNLI: A Large-scale Dataset for Document-level Natural Language Inference
Natural language inference (NLI) is formulated as a unified framework fo...
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05/18/2021
BookSum: A Collection of Datasets for Long-form Narrative Summarization
The majority of available text summarization datasets include short-form...
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02/23/2021
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
Real world applications such as economics and policy making often involv...
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10/24/2020
Unsupervised Paraphrase Generation via Dynamic Blocking
We propose Dynamic Blocking, a decoding algorithm which enables large-sc...
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09/29/2020
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
We present GraPPa, an effective pre-training approach for table semantic...
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07/30/2020
Photon: A Robust Cross-Domain Text-to-SQL System
Natural language interfaces to databases (NLIDB) democratize end user ac...
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07/24/2020
SummEval: Re-evaluating Summarization Evaluation
The scarcity of comprehensive up-to-date studies on evaluation metrics f...
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07/06/2020
DART: Open-Domain Structured Data Record to Text Generation
We introduce DART, a large dataset for open-domain structured data recor...
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10/08/2019
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
Dialog State Tracking (DST) is a core component in task-oriented dialog ...
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06/06/2019
Explain Yourself! Leveraging Language Models for Commonsense Reasoning
Deep learning models perform poorly on tasks that require commonsense re...
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05/21/2019
