All Work
Title
Topic
-
‘How Profilers Can Help Navigate Type Migration’
“Sound migratory typing envisions a safe and smooth refactoring of untyped code bases to typed ones. However, the cost of enforcing safety with run-time checks is often prohibitively high, thus performance regressions are a likely occurrence. … In principal though, migration could be guided by off-the-shelf profiling tools. To examine this hypothesis, this paper follows the rational programmer method and reports on the results of an experiment on tens of thousands of performance-debugging scenarios via seventeen strategies for turning profiler output into an actionable next step.” Find the paper and authors list in the proceedings of the ACM on Programming…
-
‘Content-Based Search for Deep Generative Models’
“The growing proliferation of customized and pretrained generative models has made it infeasible for a user to be fully cognizant of every model in existence. To address this need, we introduce the task of content-based model search: given a query and a large set of generative models, finding the models that best match the query. As each generative model produces a distribution of images, we formulate the search task as an optimization problem to select the model with the highest probability of generating similar content as the query.” Find the paper and authors list in SIGGRAPH Asia 2023 Conference Papers.
-
‘Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models’
“We present a method to create interpretable concept sliders that enable precise control over attributes in image generations from diffusion models. Our approach identifies a low-rank parameter direction corresponding to one concept while minimizing interference with other attributes. A slider is created using a small set of prompts or sample images; thus slider directions can be created for either textual or visual concepts. Concept Sliders are plug-and-play: they can be composed efficiently and continuously modulated, enabling precise control over image generation.” Find the paper and full list of authors at ArXiv.
-
‘Local Computation Algorithms for Maximum Matching: New Lower Bounds’
“We study local computation algorithms (LCA) for maximum matching. An LCA does not return its output entirely, but reveals parts of it upon query. For matchings, each query is a vertex v; the LCA should return whether v is matched — and if so to which neighbor — while spending a small time per query. In this paper, we prove that any LCA that computes a matching that is at most an additive of ϵn smaller than the maximum matching in n-vertex graphs of maximum degree Δ must take at least Δ^Ω(1/ε) time.” Find the paper and full list of authors at ArXiv.
-
‘Exponentially Faster Massively Parallel Maximal Matching’
” The study of approximate matching in the Massively Parallel Computations (MPC) model has recently seen a burst of breakthroughs. Despite this progress, we still have a limited understanding of maximal matching which is one of the central problems of parallel and distributed computing. … In this work, we close this gap by providing a novel analysis of an extremely simple algorithm, which is a variant of an algorithm conjectured to work by Czumaj, Lacki, Madry, Mitrovic, Onak, and Sankowski.” Find the paper and full list of authors at the Journal of the ACM.
-
‘An Alternative to Regulation: The Case for Public AI’
“Can governments build AI? In this paper, we describe an ongoing effort to develop ‘public AI’ — publicly accessible AI models funded, provisioned and governed by governments or other public bodies. Public AI presents both an alternative and a complement to standard regulatory approaches to AI, but it also suggests new technical and policy challenges. We present a roadmap for how the ML research community can help shape this initiative and support its implementation and how public AI can complement other responsible AI initiatives.” Find the paper and full list of authors at ArXiv.
-
‘Future Lens: Anticipating Subsequent Tokens From a Single Hidden State’
“We conjecture that hidden state vectors corresponding to individual input tokens encode information sufficient to accurately predict several tokens ahead. More concretely, in this paper we ask: Given a hidden (internal) representation of a single token at position t in an input, can we reliably anticipate the tokens that will appear at positions ≥t+2? … We find that, at some layers, we can approximate a model’s output with more than 48% accuracy with respect to its prediction of subsequent tokens through a single hidden state.” Find the paper and full list of authors at ArXiv.
-
‘Accomodating User Expressivity While Maintaining Safety for a Virtual Alcohol Misuse Counselor’
“Client-centered counseling, in which individuals are prompted to talk about their behavior, is the standard treatment for Alcohol misuse. However, open-ended conversations with virtual agent counselor raise potential safety concerns if the agent misunderstands and provides erroneous advice. … We present a hybrid dialog system that uses a machine-learning model to generate responses to individual client speech combined with a rule-based approach to transition through structured counseling sessions.” Find the paper and full list of authors in the proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents.
-
‘Influencing Health-Related Decision Making and Therapeutic Alliance With Robot Mobility and Deixis’
“Recent trends and developments in robotics have enabled socially assistive mobile robotic platforms to be deployed in everyday human lives. These robots have the ability to navigate to a user’s location and engage in multimodal interactions to serve a variety of purposes such as promoting health behavior change. … We found that robot mobility, proxemics and deictic and verbal cuing have significant positive effects on compliance with the robot’s food recommendations and resulting nutritional quality of assembled meals.” Find the paper and full list of authors in the 32nd IEEE International Conference on Robot and Human Interactive Communication proceedings.
-
‘Keeping Users Engaged During Repeated Administration of the Same Questionnaire: Using [LLMs] to Reliably Diversify Questions’
“Standardized, validated questionnaires are vital tools in HCI research and healthcare, offering dependable self-report data. However, their repeated use in longitudinal or pre-post studies can induce respondent fatigue, impacting data quality via response biases and decreased response rates. We propose utilizing large language models (LLMs) to generate diverse questionnaire versions while retaining good psychometric properties. … Our findings highlight the potential of LLM-generated variants to invigorate questionnaires, fostering engagement and interest without compromising validity.” Find the paper and full list of authors at ArXiv.
-
‘Augmented Reality as a Visualization Technique for Scholarly Publications in Astronomy: An Empirical Evaluation’
“We present a mixed methods user study evaluating augmented reality (AR) as a visualization technique for use in astronomy journal publications. This work is motivated by the highly spatial nature of scientific visualizations employed in astronomy. … In this 52-person user study, we evaluate two AR approaches … as spatial 3D visualization techniques, as compared to a baseline 3D rendering on a phone. We identify a significant difference in mental and physical workload between the two AR conditions in men and women.” Find the paper and full list of authors in the 2023 IEEE Visualization and Visual Analytics proceedings.
-
‘Conversational Assessment of Mild Cognitive Impairment with Virtual Agents’
“Over 55 million adults worldwide have dementia, a syndrome characterized by deterioration in cognitive functioning. Screening for mild cognitive impairment is important to identify dementia early to facilitate diagnosis and initiate treatment that may modify the disease trajectory. However, standard cognitive screening tools are time-consuming, require expert administration, and make people feel as if they are being tested and are thus potentially stigmatizing. … We explored cognitive ability assessments using virtual agents, in which assessments are made during conversational dialogues.” Find the paper and full list of authors in the proceedings of the 23rd ACM International Conference on Intelligent Virtual…
-
‘Changing Parent Attitudes Towards HPV Vaccination by Including Adolescents in Multiparty Counseling Using Virtual Agents’
“Parental permission is required for medical care for children, and decisions may be made without incorporating children’s views, even for adolescents. We explore the impact of including adolescents in virtual agent-based multiparty health counseling to promote Human Papillomavirus (HPV) vaccination. … We found significant pre-post increases in parent intent to vaccinate their adolescent for both versions of the agent.” Find the paper and full list of authors in the proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents.
-
‘Multiple Toddler Tracking in Indoor Videos’
“Multiple toddler tracking (MTT) involves identifying and differentiating toddlers in video footage. While conventional multi-object tracking (MOT) algorithms are adept at tracking diverse objects, toddlers pose unique challenges due to their unpredictable movements, various poses, and similar appearance. Tracking toddlers in indoor environments introduces additional complexities such as occlusions and limited fields of view. In this paper, we address the challenges of MTT and propose MTTSort, a customized method built upon the DeepSort algorithm.” Find the paper and full list of authors at ArXiv.
-
‘A Unified Approach for Resilience and Causal Responsibility With Integer Linear Programming (ILP) and LP Relaxations’
“What is a minimal set of tuples to delete from a database in order to eliminate all query answers? This problem is called ‘the resilience of a query’ and is one of the key algorithmic problems underlying various forms of reverse data management, such as view maintenance, deletion propagation and causal responsibility. A long-open question is determining the conjunctive queries (CQs) for which resilience can be solved in PTIME. We shed new light on this problem by proposing a unified Integer Linear Programming (ILP) formulation.” Find the paper and authors list in the ACM on Management of Data conference proceedings.
-
‘Zero-Shot Referring Expression Comprehension via Structural Similarity Between Images and Captions’
“Zero-shot referring expression comprehension aims at localizing bounding boxes in an image corresponding to provided textual prompts, which requires: (i) a fine-grained disentanglement of complex visual scene and textual context, and (ii) a capacity to understand relationships among disentangled entities. Unfortunately, existing large vision-language alignment (VLA) models, e.g., CLIP, struggle with both aspects so cannot be directly used for this task. To mitigate this gap, we leverage large foundation models to disentangle both images and texts into triplets in the format of (subject, predicate, object).” Find the paper and full list of authors at ArXiv.
-
When it comes to building more resilient structures, it takes ‘a whole profession,’ Northeastern professor says
CDM Smith Professor and chair of civil and environmental engineering Jerome Hajjar received both the AISC Special Achievement Award and the SSRC Beedle Award at the recent AISC annual conference, delivering a keynote to several thousand attendees on sustainable and resilient structural systems.
-
‘Through the Looking Glass: The Role of Virtual Mirrors in Shaping Empathy in Virtual Reality Perspective Taking’
“In this study, we explored the effect of seeing one’s avatar in a virtual mirror during a virtual reality (VR) perspective taking experience. Participants were divided into two groups, with one experiencing the VR environment with the presence of a mirror showcasing their avatar and the other without. … However, a notable difference emerged in terms of empathy; participants who viewed their avatars in the mirror exhibited reduced empathic responses. These findings illuminate the nuanced dynamics of self-representation in virtual environments.” Find the paper and list of authors in the proceedings of the 22nd International Conference on Mobile and Ubiquitous…
-
‘Point and Select: Effects of Multimodal Feedback on Text Entry Performance in Virtual Reality’
“The current study examined the effects of visual, auditory, and haptic feedback on VR text entry performance and perceived mental workload across two experiments. In Experiment 1, the feedback was presented as users were pointing from one key to another, dubbed pointing feedback. … In Experiment 2, the feedback was provided when users selected the keys by pressing the trigger on the controller, dubbed selection feedback. … These results indicate that the usability of VR text entry tasks changes as a function of when and how feedback is provided.” Find the paper and authors list in the International Journal of…
-
‘Strata Fee Management in Condominiums via Smart Contracts’
“Condominiums and similar properties use a stratum to manage daily operations, and owners fund it through strata fees. While existing strata fee management systems may be able to handle such funds, such systems could be more inherently transparent. It is possible to leverage the digital ledger from blockchain networks and smart contracts to build a fully transparent strata fee management system. This paper proposes designing a strata fee management system based on a smart contract in the Ethereum network.” Find the paper and full list of authors in the Journal of Theoretical and Applied Electronic Commerce Research.
-
‘Query Efficient Weighted Stochastic Matching’
“In this paper, we study the weighted stochastic matching problem. Let G=(V,E) be a given edge-weighted graph and let its realization G be a random subgraph of G that includes each edge e∈E independently with a known probability pe. The goal in this problem is to pick a sparse subgraph Q of G without prior knowledge of G’s realization, such that the maximum weight matching among the realized edges of Q (i.e. the subgraph Q∩) in expectation approximates the maximum weight matching of the entire realization G.” Find the paper and full list of authors at ArXiv.
-
‘HypOp: Distributed Constrained Combinatorial Optimization Leveraging Hypergraph Neural Networks’
“Scalable addressing of high dimensional constrained combinatorial optimization problems is a challenge that arises in several science and engineering disciplines. Recent work introduced novel application of graph neural networks for solving polynomial-cost unconstrained combinatorial optimization problems. This paper proposes a new framework, called HypOp, which greatly advances the state of the art for solving combinatorial optimization problems in several aspects.” Find the paper and full list of authors at ArXiv.
-
Hip-hop may be a house ‘that young people built,’ but ‘Hip-Hop Archives’ are here for everyone
Professor of communication studies Murray Forman has co-edited “Hip-Hop Archives: The Politics and Poetics of Knowledge Production,” which collects scholarship on modern archival practices in hip-hop culture, espousing multi-generational collaborations in archives that scale in size from government institutions to bedroom closets.
-
Professor’s new book shines light on how architectural works are in constant conversation with the past
With “The Architecture of Influence,” associate professor of architecture Amanda Lawrence explores how architectural copies, imitations, emulations and more interact to create an ongoing conversation between the present and the past.
-
‘Design Rules for Optimization of Photophysical and Kinetic Properties of Azoarene Photoswitches’
“Azoarenes are an important class of molecular photoswitches that often undergo E → Z isomerization with ultraviolet light and have short Z-isomer lifetimes. Azobenzene has been a widely studied photoswitch for decades but can be poorly suited for photopharmacological applications due to its UV-light absorption and short-lived Z-isomer half-life (t1/2). … We calculated the E-isomer absorption (λmax) and Z-isomer t1/2 for a set of 26 hemi-azothiophenes. We compared their properties to thiophene-based photoswitches that have been studied previously.” Find the paper and full list of authors at Organic and Biomolecular Chemistry.
-
‘Reanalysis of mtDNA mutations of human primordial germ cells (PGCs) reveals NUMT contamination … selection in PGCs may be positive’
“The resilience of the mitochondrial genome (mtDNA) to a high mutational pressure depends, in part, on negative purifying selection in the germline. A paradigm in the field has been that such selection, at least in part, takes place in primordial germ cells (PGCs). Specifically, Floros et al. (Nature Cell Biology 20: 144-51) reported an increase in the synonymity of mtDNA mutations (a sign of purifying selection) between early-stage and late-stage PGCs. We re-analyzed Floros’ et al. data and determined that their mutational dataset was significantly contaminated with single nucleotide variants.” Find the paper and full list of authors in Mitochondrion.
-
‘Allosteric Site Variants Affect GTP Hydrolysis on Ras’
“RAS GTPases are proto‐oncoproteins that regulate cell growth, proliferation and differentiation in response to extracellular signals. The signaling functions of RAS, and other small GTPases, are dependent on their ability to cycle between GDP‐bound and GTP‐bound states. … GTP hydrolysis catalyzed by HRAS can be regulated by an allosteric site located between helices 3, 4 and loop 7. Here we explore the relationship between intrinsic GTP hydrolysis on HRAS and the position of helix 3 and loop 7 through manipulation of the allosteric site, showing that the two sites are functionally connected.” Find the paper and authors list at Protein…
-
‘Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic’
“The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes. … Here, we characterize collective physical distancing … in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users’ mobility and proximity to investigate how the emerging collective behavior deviates from typical pre-pandemic patterns during the first nine months of the COVID-19 pandemic.” Find the paper and full list of authors at PLOS Digital Health.