140 citations · 215 across the 18 of their papers we have counts for
20 papers
Longitudinal Brain Aging in Covariance Space: Temporally Calibrated Bayesian Inference for Adaptive Covariance Operators
Montserrat Fuentes, Yi Zhao
Functional brain aging is often characterized by differences between people of different ages, although aging unfolds within individuals. This distinction is especially important f…
WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution
Liyan Tang, Cyrus Rashtchian, Chun-Sung Ferng +3
Agent skills package specialized knowledge and workflows into reusable resources that extend AI agent capabilities. Recent work automatically discovers such skills from agent exper…
On the Generalization Gap in Self-Evolving Language Model Reasoning
Zhenting Qi, Susanna Maria Baby, Stefanie Anna Baby +5
Recent work suggests that large language models (LLMs) can improve through self-evolution (SE), using supervision signals generated by the model itself. In this work, we ask: under…
Substance or Style: What Does Your Image Embedding Know?
Cyrus Rashtchian, Charles Herrmann, Chun-Sung Ferng +5
Probes are small networks that predict properties of underlying data from embeddings, and they provide a targeted, effective way to illuminate the information contained in embeddin…
An Efficient Simulation-Based Travel Demand Calibration Algorithm for Large-Scale Metropolitan Traffic Models
Neha Arora, Yi-fan Chen, Sanjay Ganapathy +5
Metropolitan scale vehicular traffic modeling is used by a variety of private and public sector urban mobility stakeholders to inform the design and operations of road networks. Hi…
CARLS: Cross-platform Asynchronous Representation Learning System
Chun-Ta Lu, Yun Zeng, Da-Cheng Juan +13
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge make…
Graph Autoencoders with Deconvolutional Networks
Jia Li, Tomas Yu, Da-Cheng Juan +3
Recent studies have indicated that Graph Convolutional Networks (GCNs) act as a \emph{low pass} filter in spectral domain and encode smoothed node representations. In this paper, w…
Adversarial Robustness Across Representation Spaces
Pranjal Awasthi, George Yu, Chun-Sung Ferng +2
Adversarial robustness corresponds to the susceptibility of deep neural networks to imperceptible perturbations made at test time. In the context of image tasks, many algorithms ha…
Surprise: Result List Truncation via Extreme Value Theory
Dara Bahri, Che Zheng, Yi Tay +2
Work in information retrieval has largely been centered around ranking and relevance: given a query, return some number of results ordered by relevance to the user. The problem of…
Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study
Dara Bahri, Yi Tay, Che Zheng +3
Large generative language models such as GPT-2 are well-known for their ability to generate text as well as their utility in supervised downstream tasks via fine-tuning. Our work i…
BusTr: Predicting Bus Travel Times from Real-Time Traffic
Richard Barnes, Senaka Buthpitiya, James Cook +3
We present BusTr, a machine-learned model for translating road traffic forecasts into predictions of bus delays, used by Google Maps to serve the majority of the world's public tra…
Choppy: Cut Transformer For Ranked List Truncation
Dara Bahri, Yi Tay, Che Zheng +2
Work in information retrieval has traditionally focused on ranking and relevance: given a query, return some number of results ordered by relevance to the user. However, the proble…
Reverse Engineering Configurations of Neural Text Generation Models
Yi Tay, Dara Bahri, Che Zheng +3
This paper seeks to develop a deeper understanding of the fundamental properties of neural text generations models. The study of artifacts that emerge in machine generated text as…
Preventing Adversarial Use of Datasets through Fair Core-Set Construction
Benjamin Spector, Ravi Kumar, Andrew Tomkins
We propose improving the privacy properties of a dataset by publishing only a strategically chosen "core-set" of the data containing a subset of the instances. The core-set allows…
Graph-RISE: Graph-Regularized Image Semantic Embedding
Da-Cheng Juan, Chun-Ta Lu, Zhen Li +7
Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering. In this p…
SCRank: Spammer and Celebrity Ranking in Directed Social Networks
Alex Fabrikant, Mohammad Mahdian, Andrew Tomkins
Many online social networks allow directed edges: Alice can unilaterally add an "edge" to Bob, typically indicating interest in Bob or Bob's content, without Bob's permission or re…
Linear Additive Markov Processes
Ravi Kumar, Maithra Raghu, Tamas Sarlos +1
We introduce LAMP: the Linear Additive Markov Process. Transitions in LAMP may be influenced by states visited in the distant history of the process, but unlike higher-order Markov…
Single versus Double Blind Reviewing at WSDM 2017
Andrew Tomkins, Min Zhang, William D. Heavlin
In this paper we study the implications for conference program committees of using single-blind reviewing, in which committee members are aware of the names and affiliations of pap…
Smart Reply: Automated Response Suggestion for Email
Anjuli Kannan, Karol Kurach, Sujith Ravi +8
In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply. It generates semantically diverse suggest…
Your Two Weeks of Fame and Your Grandmother's
James Cook, Atish Das Sarma, Alex Fabrikant +1
Did celebrity last longer in 1929, 1992 or 2009? We investigate the phenomenon of fame by mining a collection of news articles that spans the twentieth century, and also perform a…