Title
Topic
-
Engineering professor wants to revolutionize wireless communication by manipulating ‘acoustic waves in solids’
Assistant professor of electrical and computer engineering Siddhartha Ghosh has received two prestigious early career awards for his work on radio frequency front-end devices, developing materials that convert radio signals into acoustic waves at the microchip level.
-
‘Black-Box Access is Insufficient for Rigorous AI Audits’
“External audits of AI systems are increasingly recognized as a key mechanism for AI governance. The effectiveness of an audit, however, depends on the degree of system access granted to auditors. Recent audits of state-of-the-art AI systems have primarily relied on black-box access, in which auditors can only query the system and observe its outputs. However, white-box access to the system’s inner workings … allows an auditor to perform stronger attacks. … In this paper, we examine the limitations of black-box audits and the advantages of white- and outside-the-box audits.” Find the paper and full list of authors at ArXiv.
-
‘Deploying and Evaluating LLMs to Program Service Mobile Robots’
“Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We investigate the use of LLMs to generate programs for service mobile robots leveraging mobility, perception and human interaction skills, and where accurate sequencing and ordering of actions is crucial for success. We contribute CodeBotler, an open-source robot-agnostic tool to program service mobile robots from natural language, and RoboEval , a benchmark for evaluating LLMs’ capabilities of generating programs to complete service robot tasks.” Find the paper and list of authors at IEEE Robotics and Automation…
-
‘How Beginning Programmers and Code LLMs (Mis)read Each Other’
“Generative AI models, specifically large language models (LLMs), have made strides towards the long-standing goal of text-to-code generation. This progress has invited numerous studies of user interaction. However, less is known about the struggles and strategies of non-experts, for whom each step of the text-to-code problem presents challenges: describing their intent in natural language, evaluating the correctness of generated code, and editing prompts when the generated code is incorrect. This paper presents a large-scale controlled study of how 120 beginning coders across three academic institutions approach writing and editing prompts.” Find the paper and full list of authors at ArXiv.
-
Ocean Genome Legacy Center receives grant in support of student research
The Ocean Genome Legacy Center (OGL) has a received a grant from Cell Signaling Technology “providing funds for [student] experiments to improve the quality of DNA extracted from frozen biological materials.” Capitalizing on previous hypotheses made by OGL students, they are now “testing what happens if frozen tissue is thawed overnight in chilled liquid preservatives instead of extracting DNA directly from frozen tissue” in order to prevent DNA degradation.
-
Wanunu receives patent for hybrid nanopores
Professor of physics and bioengineering Meni Wanunu has received a patent for “Hybrid nanopores, comprising a protein pore supported within a solid-state membrane,” according to the patent’s abstract. “In an embodiment,” the abstract continues, “a lipid-free hybrid nanopore comprises a water soluble and stable, modified portal protein of the Thermus thermophilus bacteriophage G20c, electrokinetically inserted into a larger nanopore in a solid-state membrane. The hybrid pore is stable and easy to fabricate, and exhibits low peripheral leakage, allowing sensing and discrimination among different types of biomolecules.”
-
‘Early life adversity accelerates hypothalamic drive of pubertal timing in female rats with associated enhanced acoustic startle’
“Early life adversity in the form of childhood maltreatment in humans or as modeled by maternal separation (MS) in rodents is often associated with an earlier emergence of puberty in females. Earlier pubertal initiation is an example of accelerated biological aging and predicts later risk for anxiety in women, especially in populations exposed to early life trauma. … These findings indicate precocial maturation of central pubertal timing mechanisms after MS, as well as a potential role of CRH-R1 in these effects and an association with a translational measure of anxiety.” Find the paper and list of authors at Hormones and…
-
‘Solid-State Sensors’ invites ‘advanced students’ into the field
Ravinder Dahiya, professor of electrical and computer engineering, with co-authors Ambarish Paul and Mitradip Bhattacharjee, has published “Solid-State Sensors,” an “up-to-date introduction to solid-state sensors, materials, fabrication processes and applications,” according to the publisher’s webpage. Oriented toward “advanced students and professionals in disciplines such as electrical and electronics engineering, physics, chemistry and biomedical engineering,” the textbook includes “the fundamentals and classification of all major types of solid-state sensors, including piezoresistive, capacitive, thermometric, optical bio-chemical, magnetic and acoustic-based sensors.”
-
Large language models can lie to you — this professor wants you to know when they do
Assistant professor of computer science Malihe Alikhani has received a DARPA AI Exploration grant to introduce “healthy frictions” into human-AI interactions. These frictions would help human users understand the varying levels of certainty large language models have regarding their own statements and decrease the likelihood of users falling for AI “hallucinations.”
-
‘Top-Down Control Over Dissolved Organic Carbon in the Bottom Water of the Weddell Sea and its Implication for the Continental Shelf Pump’
“Dense water out of the Antarctic shelves is expected to drive the transport of carbon into the deep Southern Ocean via the formation of Antarctic Bottom Water. However, bottom water formation’s capacity to sequester carbon into the deep ocean is poorly constrained. Here, dissolved organic carbon (DOC), dissolved black carbon and particulate organic carbon were examined to reveal the influence of the Weddell Sea Deep Water on DOC transport. … This study highlights the key role of the Antarctic continental shelf pump in carbon sequestration.” Find the paper and authors list at Progress in Oceanography.
-
‘Local and Regional Geographic Variation in Inducible Defenses’
“Invasive predators can cause substantial evolutionary change in native prey populations. … Our ability to understand how local variation shapes patterns of inducible defense expression has thus far been limited by insufficient replication of populations within regions. Here, we examined local and regional variation in the inducible defenses of 12 native marine snail (Littorina obtusata) populations within two geographic regions in the Gulf of Maine that are characterized by vastly different contact histories with the invasive predatory green crab (Carcinus maenas).” Find the paper and full list of authors in Ecology.
-
‘ICML 2023 Topological Deep Learning Challenge: Design and Results’
“This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two month duration. This paper describes the design of the challenge and summarizes its main findings.” Find the paper and full list of authors at Proceedings of Machine Learning Research.
-
‘Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture’
“Real-world domain experts (e.g., doctors) rarely annotate only a decision label in their day-to-day workflow without providing explanations. Yet, existing low-resource learning techniques, such as Active Learning (AL), that aim to support human annotators mostly focus on the label while neglecting the natural language explanation of a data point. This work proposes a novel AL architecture to support experts’ real-world need for label and explanation annotations in low-resource scenarios.” Find the paper and full list of authors in the Findings of the Association for Computational Linguistics.
-
‘Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks’
“Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance. However, in real-world tasks, domain knowledge is often required. … In this work, we conduct an empirical experiment on four datasets from three different domains comparing SOTA LLMs with small models trained on expert annotations with [Active Learning]. We found that small models can outperform GPT-3.5 with a few hundreds of labeled data, and they achieve higher or similar performance with GPT-4 despite that they are hundreds time smaller.” Find the paper and full list of authors at ArXiv.
-
‘”The Wallpaper is Ugly”: Indoor Localization Using Vision and Language’
“We study the task of locating a user in a mapped indoor environment using natural language queries and images from the environment. Building on recent pretrained vision-language models, we learn a similarity score between text descriptions and images of locations in the environment. … Our approach is capable of localizing on environments, text, and images that were not seen during training. One model, finetuned CLIP, outperformed humans in our evaluation.” Find the paper and full list of authors in the 32nd IEEE International Conference on Robot and Human Interactive Communication proceedings.
-
‘Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education’
“Despite the promises of ML in education, its adoption in the classroom has surfaced numerous issues. … A root cause of these issues is the lack of understanding of the complex dynamics of education, including teacher-student interactions, collaborative learning and classroom environment. To overcome these challenges … software practitioners need to work closely with educators and students to fully understand the context of the data (the backbone of ML applications) and collaboratively define the ML data specifications. … We conduct ten co-design sessions with ML software practitioners, educators and students.” Find the paper and full list of authors at ArXiv.
-
‘Multi-Instance Randomness Extraction and Security Against Bounded-Storage Mass Surveillance’
“Consider a state-level adversary who observes and stores large amounts of encrypted data from all users on the Internet, but does not have the capacity to store it all. Later, it may target certain ‘persons of interest.’ … We would like to guarantee that, if the adversary’s storage capacity is only (say) 1% of the total encrypted data size, then even if it can later obtain the decryption keys of arbitrary users, it can only learn something about the contents of (roughly) 1% of the ciphertexts.” Find the paper and authors list at Theory of Cryptography.
-
‘More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering’
“While most existing works on LLM prompting techniques focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can not we design and leverage multiple prompts together to further improve the LLM’s performance? In this work, we propose In-Context Sampling (ICS), a low-resource LLM prompting technique to produce confident predictions by optimizing the construction of multiple ICL prompt inputs.” Find the paper and full list of authors at ArXiv.
-
‘Bergeron: Combating Adversarial Attacks Through a Conscience-Based Alignment Framework’
“Research into AI alignment has grown considerably since the recent introduction of increasingly capable Large Language Models (LLMs). Unfortunately, modern methods of alignment still fail to fully prevent harmful responses when models are deliberately attacked. These attacks can trick seemingly aligned models into giving manufacturing instructions for dangerous materials, inciting violence, or recommending other immoral acts. To help mitigate this issue, we introduce Bergeron: a framework designed to improve the robustness of LLMs against attacks without any additional parameter fine-tuning.” Find the paper and full list of authors at ArXiv.
-
‘Hierarchical RL-Guided Large-Scale Navigation of a Snake Robot’
“Classical snake robot control leverages mimicking snake-like gaits tuned for specific environments. However, to operate adaptively in unstructured environments, gait generation must be dynamically scheduled. In this work, we present a four-layer hierarchical control scheme to enable the snake robot to navigate freely in large-scale environments. The proposed model decomposes navigation into global planning, local planning, gait generation and gait tracking. Using reinforcement learning (RL) and a central pattern generator (CPG), our method learns to navigate in complex mazes within hours.” Find the paper and full list of authors at ArXiv.
-
‘On Tolerance of Discrete Systems With Respect to Transition Perturbations’
“Control systems should enforce a desired property for both expected/modeled situations as well as unexpected/unmodeled environmental situations. Existing methods focus on designing controllers to enforce the desired property only when the environment behaves as expected. However, these methods lack discussion on how the system behaves when the environment is perturbed. In this paper, we propose an approach for analyzing discrete-state control systems with respect to their tolerance against environmental perturbations.” Find the paper and full list of authors in Discrete Event Dynamic Systems.
-
‘Code Coverage Criteria for Asynchronous Programs’
“Asynchronous software often exhibits complex and error-prone behaviors that should be tested thoroughly. … Traditional code coverage criteria do not adequately reflect completion, interactions and error handling of asynchronous operations. This paper proposes novel test adequacy criteria for measuring: (i) completion of asynchronous operations in terms of both successful and exceptional execution, (ii) registration of reactions for handling both possible outcomes and (iii) execution of said reactions through tests.” Find the paper and full list of authors in the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
-
‘Increasing the Responsiveness of Web Applications by Introducing Lazy Loading’
“Front-end developers want their applications to contain no more code than is needed in order to minimize the amount of time that elapses between visiting a web page and the page becoming responsive. However, front-end code is typically written in JavaScript … and tends to rely heavily on third-party packages. … One way to combat such bloat is to lazily load external packages on an as-needed basis. … In this work, we propose an approach for automatically introducing lazy loading of third-party packages in JavaScript applications.” Find the paper and authors list in the 2023 IEEE International Conference on Automated…
-
‘Testing the Limits of Neural Sentence Alignment Models on Classical Greek and Latin Texts and Translations’
“The Greek and Latin classics, like many other ancient texts, have been widely translated into a variety of languages over the past two millennia. … Aligning the corpus of classical texts and translations at the sentence and word level would provide a valuable resource for studying translation theory, digital humanities and natural language processing (NLP). … This paper evaluates and examines the limits of such state-of-the-art models for cross-language sentence embedding and alignment of ancient Greek and Latin texts with translations into English, French, German and Persian.” Find the paper and authors list in the Computational Humanities Research Conference 2023…
-
‘Automatic Collation for Diversifying Corpora: Commonly Copied Texts as Distant Supervision for Handwritten Text Recognition’
“Handwritten text recognition (HTR) has enabled many researchers to gather textual evidence from the human record. … To build generalized models for Arabic-script manuscripts, perhaps one of the largest textual traditions in the pre-modern world, we need an approach that can improve its accuracy on unseen manuscripts and hands without linear growth in the amount of manually annotated data. We propose Automatic Collation for Diversifying Corpora (ACDC), taking advantage of the existence of multiple manuscripts of popular texts.” Find the paper and full list of authors in the Computational Humanities Research Conference 2023 proceedings.
-
‘Proving Calculational Proofs Correct’
“Teaching proofs is a crucial component of any undergraduate-level program that covers formal reasoning. We have developed a calculational reasoning format and refined it over several years of teaching a freshman-level course, ‘Logic and Computation,’ to thousands of undergraduate students. In our companion paper, we presented our calculational proof format [and] gave an overview of the calculational proof checker (CPC) tool that we developed. … In this paper, we dive deeper into the implementation details of CPC, highlighting how proof validation works, which helps us argue that our proof checking process is sound.” Find the paper and authors list at…
-
‘Verification of GossipSub in ACL2s’
“GossipSub is a popular new peer-to-peer network protocol designed to disseminate messages quickly and efficiently by allowing peers to forward the full content of messages only to a dynamically selected subset of their neighboring peers (mesh neighbors) while gossiping about messages they have seen with the rest. Peers decide which of their neighbors to graft or prune from their mesh locally and periodically using a score for each neighbor. … In this paper, we present a detailed description of our model.” Find the paper and full list of authors at ArXiv.
-
‘Using Counterexample Generation and Theory Exploration To Suggest Missing Hypotheses’
“Newcomers to ACL2 are sometimes surprised that ACL2 rejects formulas that they believe should be theorems. … Counterexample generation (cgen) is a technique that helps by giving the user a number of counterexamples (and also witnesses) to the formula, e.g., letting the user know that the intended theorem is false when X is equal to 10. In this paper we describe a tool called DrLA that goes further by suggesting additional hypotheses that will make the theorem true.” Find the paper and full list of authors at ArXiv.
-
‘A Case Study in Analytic Protocol Analysis in ACL2’
“When verifying computer systems we sometimes want to study their asymptotic behaviors, i.e., how they behave in the long run. In such cases, we need real analysis, the area of mathematics that deals with limits and the foundations of calculus. In a prior work, we used real analysis in ACL2s to study the asymptotic behavior of the RTO computation. … In this paper, we explore different approaches to proving the above result in ACL2(r) and ACL2s, from the perspective of a relatively new user to each.” Find the paper and full list of authors at ArXiv.