Graphs play a crucial role in many applications, ranging from drug discovery to social network modeling and astronomy. Generative models for graphs have substantially advanced in recent years, but we identify relatively simple scenarios where state-of-the-art models struggle to converge within a standard compute budget...
D. Micheletti, Federica Zoe Ricci, Erik B. Sudderth· 0 citations
Replacing the judge can move a benchmark score, and models can be trained to hide capabilities. Both put the evaluator in question: what can it certify? We develop a partition theory of evaluation from one principle: judgement is bounded by perception. An agent's discrimination is the partition of its inputs into class...
LLVMhammer is presented, the first Rowhammer attack that causes LLM inference slowdown by inducing a bit-flip in Triton's compilation pipeline and it is shown that LLVMhammer can also corrupt LLM outputs across different GPU vendors, reducing BERTScore to as low as 25\%, illustrating the broader security implications o...
This paper presents AIRO (Autonomous Intelligence-Driven Cybersecurity Risk Re- duction System), an efficient framework for IIoT monitoring and response that combines Apache Kafka streaming, attack- specific feature extraction, machine learning (ML) inference, confidence-based decision logic and risk reduction measures...
Raima Deb, P. Pawar, Mithun Mukherjee et al.· 0 citations
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Six new safety datasets of sufficient size and difficulty are constructed and it is found that probe error follows two simple scaling laws, which allow safety researchers to determine how to create the best probe for any given model and label budget.
Iterative combinatorial auctions are used in spectrum allocation, transportation, and industrial procurement, but rounds are costly. We introduce FastCombo, a deep reinforcement learning approach to sequential price discovery. Bayesian pricing has sharply reduced auction rounds even against subgradient benchmarks tuned...
Luis F. Paul Tosta, Quinn Arnold, Gianluca Brero· 0 citations
This work proposes a Hybrid Fuzzy Ensemble that synergizes the precision of supervised learning with the adaptability of unsupervised clustering, and introduces a robust Min Distance metric that exploits the raw geometric isolation of botnet activation attacks.
Lohith Srikanth Pentapalli, J. Riep, Justin N. Ouwerkerk et al.· 0 citations
AI agents increasingly act as analysts whose decision can often be cast as hypothesis tests. Classical tests control the Type I error rate, the probability of rejecting a true null hypothesis, for fixed procedures. However, AI analysts introduce internal randomness and can evolve continuously over time. As AI analysts...
Predicting surrounding vehicles'lane-change intentions enables autonomous vehicles to anticipate potential hazards and respond proactively rather than relying solely on reactive maneuvers. This study investigates the benefits of integrating lane-change prediction, based on knowledge graph embeddings and Bayesian infere...
Mohamed A. Manzour, Aditya Kumar, R. Izquierdo et al.· 0 citations
Lyapunov functions and barrier certificates give state-space guarantees of stability and safety, but synthesizing and verifying them---especially for nonlinear, high-dimensional systems---remains an open challenge. Existing pipelines verify candidates with numerical solvers (sum-of-squares programs), interval methods,...
Zhipeng Cao, Peiyang Song, Nikolaus Vertovec et al.· 0 citations
Weight-only quantization keeps LLM activations in floating point and stores weights as low-bit integers, turning the dominant workload into floating-point-integer (FP-INT) general matrix multiplication. Recent quantizers reach a 2-3-bit average with mixed precision, but hardware has not kept pace: GPUs dequantize weigh...
Faraz Tahmasebi, Haocheng Xu, Andrew Trauger et al.· 0 citations
Traffic management has traditionally focused on toll-based and road pricing solutions. However, road pricing often raises concerns about accessibility and public dissatisfaction, leading to its prohibition in some places, such as Finland. This study optimises the dynamic allocation of incentives to drivers, encouraging...
Germ\'an Pardo-Gonz\'alez, Shaghayegh Vosough, Katerina Papadaki et al.· 0 citations
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
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