research
∙
08/08/2023
FLIRT: Feedback Loop In-context Red Teaming
Warning: this paper contains content that may be inappropriate or offens...
share
research
∙
06/06/2023
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs
Measurement of interaction quality is a critical task for the improvemen...
research
∙
05/30/2023
History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion
Temporal knowledge graph (TKG) completion models typically rely on havin...
research
∙
05/26/2023
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation
Paraphrase generation is a long-standing task in natural language proces...
research
∙
05/23/2023
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding
Conversational AI systems such as Alexa need to understand defective que...
research
∙
05/17/2023
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation
Transgender and non-binary (TGNB) individuals disproportionately experie...
research
∙
05/12/2023
ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems
Commonsense reasoning is omnipresent in human communications and thus is...
research
∙
11/17/2022
Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models
Natural language often contains ambiguities that can lead to misinterpre...
research
∙
11/02/2022
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations
Syntactically controlled paraphrase generation has become an emerging re...
research
∙
10/07/2022
An Analysis of the Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation
Several prior works have shown that language models (LMs) can generate t...
research
∙
03/25/2022
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations
Multiple metrics have been introduced to measure fairness in various nat...
research
∙
03/18/2022
DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations
Automatic evaluation metrics are essential for the rapid development of ...
research
∙
11/03/2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
Sampling from an unnormalized probability distribution is a fundamental ...
research
∙
10/09/2021
Cognitively Inspired Learning of Incremental Drifting Concepts
Humans continually expand their learned knowledge to new domains and lea...
research
∙
10/04/2021
Information-theoretic generalization bounds for black-box learning algorithms
We derive information-theoretic generalization bounds for supervised lea...
research
∙
07/04/2021
Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation
Sentiment analysis is a costly yet necessary task for enterprises to stu...
research
∙
07/01/2021
q-Paths: Generalizing the Geometric Annealing Path using Power Means
Many common machine learning methods involve the geometric annealing pat...
research
∙
04/12/2021
Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation
With the recent advances of open-domain story generation, the lack of re...
research
∙
02/17/2021
Fast Graph Learning with Unique Optimal Solutions
Graph Representation Learning (GRL) has been advancing at an unprecedent...
research
∙
02/08/2021
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Graph Representation Learning (GRL) methods have impacted fields from ch...
research
∙
02/03/2021
DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation
Having engaging and informative conversations with users is the utmost g...
research
∙
12/31/2020
Likelihood Ratio Exponential Families
The exponential family is well known in machine learning and statistical...
research
∙
12/14/2020
Annealed Importance Sampling with q-Paths
Annealed importance sampling (AIS) is the gold standard for estimating p...
research
∙
11/30/2020
MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization
Deep neural networks are powerful, massively parameterized machine learn...
research
∙
07/29/2020
Compressing Deep Neural Networks via Layer Fusion
This paper proposes layer fusion - a model compression technique that di...
research
∙
07/10/2020
Robust Classification under Class-Dependent Domain Shift
Investigation of machine learning algorithms robust to changes between t...
research
∙
07/01/2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
The recently proposed Thermodynamic Variational Objective (TVO) leverage...
research
∙
07/01/2020
Sequential Unsupervised Domain Adaptation through Prototypical Distributions
We develop an algorithm for unsupervised domain adaptation (UDA) of a cl...
research
∙
05/05/2020
Event Cartography: Latent Point Process Embeddings
Many important phenomena arise naturally as temporal point processes wit...
research
∙
03/03/2020
Anchor Attention for Hybrid Crowd Forecasts Aggregation
Forecasting the future is a notoriously difficult task. To overcome this...
research
∙
02/19/2020
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights
In the presence of noisy or incorrect labels, neural networks have the u...
research
∙
02/09/2020
Towards Learning Representations of Binary Executable Files for Security Tasks
Tackling binary analysis problems has traditionally implied manually def...
research
∙
11/04/2019
Predictive Engagement: An Efficient Metric For Automatic Evaluation of Open-Domain Dialogue Systems
User engagement is a critical metric for evaluating the quality of open-...
research
∙
10/24/2019
Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity Recognition
We study the bias in several state-of-the-art named entity recognition (...
research
∙
09/22/2019
Deep Structured Neural Network for Event Temporal Relation Extraction
We propose a novel deep structured learning framework for event temporal...
research
∙
09/17/2019
Stacking Models for Nearly Optimal Link Prediction in Complex Networks
Most real-world networks are incompletely observed. Algorithms that can ...
research
∙
09/09/2019
Nearly-Unsupervised Hashcode Representations for Relation Extraction
Recently, kernelized locality sensitive hashcodes have been successfully...
research
∙
08/23/2019
A Survey on Bias and Fairness in Machine Learning
With the widespread use of AI systems and applications in our everyday l...
research
∙
05/30/2019
Efficient Covariance Estimation from Temporal Data
Estimating the covariance structure of multivariate time series is a fun...
research
∙
04/30/2019
MixHop: Higher-Order Graph Convolution Architectures via Sparsified Neighborhood Mixing
Existing popular methods for semi-supervised learning with Graph Neural ...
research
∙
04/24/2019
Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings
Despite advances in open-domain dialogue systems, automatic evaluation o...
research
∙
04/15/2019
Exact Rate-Distortion in Autoencoders via Echo Noise
Compression is at the heart of effective representation learning. Howeve...
research
∙
02/04/2019
Identifying and Analyzing Cryptocurrency Manipulations in Social Media
Interest surrounding cryptocurrencies, digital or virtual currencies tha...
research
∙
11/27/2018
Maximizing Multivariate Information with Error-Correcting Codes
Multivariate mutual information provides a conceptual framework for char...
research
∙
05/24/2018
Evading the Adversary in Invariant Representation
Representations of data that are invariant to changes in specified nuisa...
research
∙
05/17/2018
A Forest Mixture Bound for Block-Free Parallel Inference
Coordinate ascent variational inference is an important algorithm for in...
research
∙
04/26/2018
Dialogue Modeling Via Hash Functions: Applications to Psychotherapy
We propose a novel machine-learning framework for dialogue modeling whic...
research
∙
03/18/2018
Adaptive prior probabilities via optimization of risk and entropy
An agent choosing between various actions tends to take the one with the...
research
∙
02/16/2018
Auto-Encoding Total Correlation Explanation
Advances in unsupervised learning enable reconstruction and generation o...
research
∙
01/11/2018
