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17,191 papers
Code-to-architecture mapping assigns source files to modules of a reference architecture. Representations of implementation artifacts can capture code text, dependencies, and directory organization, but predictive gains alone do not establish the contribution of additional graph processing. Dependencies may already be...
Finding optimal transport protocols for underdamped stochastic processes is a difficult yet important problem in control theory. In this paper we develop a direct method, based on machine learning, to find the optimal solution of the problem in the presence of non-linear boundary conditions, including those modelling t...
This study proposes PDE-residual-informed Kriging (PRIK) based on a PDE-residual kernel, which makes PRIK yield the posterior mean with minimum integrated squared PDE residual, and establishes regularity and stability conditions for the posterior mean, together with a nonasymptotic bound for its PDE-residual norm.
Direct Preference Optimization (DPO) treats every reported comparison as correct, yet preference data contain reversed, tied or otherwise noisy comparisons. RW-DPO gives each comparison an unknown reliability weight $w_i\in[0,1]$ that enters the likelihood linearly -- DPO is $w\equiv1$, a reversed comparison $w_i=0...
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Unlike autoregressive (AR) models, diffusion language models (DLMs) permit parallel token updates, flexible generation, and bidirectional attention, but leading systems rely on costly pretraining or full-model fine-tuning. We present Build Your Own DLM (BYOD), a generalizable LoRA-only recipe for parameter-efficient AR...
DeepWeave is presented, a probabilistic neuro-symbolic Network Intrusion Detection System (NIDS) that makes logic an integral part of detection, and demonstrates label-efficient, adaptable, and inspectable neuro-symbolic intrusion detection.
DAPS, a dependency-aware premise selector with a structural neighborhood encoder, a group-level contrastive objective, and a Mathlib-then-Blueprint adaptation procedure is introduced, and experiments demonstrate that DAPS premises improve theorem proving on miniF2F and IMO-ProofBench.
Fine-tuning a language model changes how it responds, but where is this fine-tuned behavior instantiated? To better understand this, we evaluate whether the change in model behavior arises only during the generation of the answer tokens where the change manifests, or whether altered processing of previous tokens causes...
Patients often arrive at brief, time-constrained clinical visits unsure of what to expect or ask, and millions of adults now turn to general-purpose AI chatbots to prepare beforehand. Yet whether conversational AI improves visit readiness remains unclear. We designed a large language model (LLM)-based visit preparation...
SACQ is introduced, an ultra- low-bit weight-only vector-codebook quantization framework for VLAs that combines structure-aware codebook fitting with role-specific quadratic metrics that reflect input statistics and downstream sensitivity.
Conditional generation of time-series paths is a central problem in probabilistic modeling, where the goal is to simulate future trajectories that are both realistic and responsive to external context. It has direct applications in finance and economics. Neural stochastic differential equations provide a natural framew...
DUGO (Dual-Scale Encoding and Gaussian Memory Online), a new OnTAL framework that jointly models local motion dynamics and long-range temporal dependencies, uses a Dual-Scale Temporal Encoder and introduces a Gaussian Memory Bank, which represents action memory as stochastic, input-conditioned Gaussian prototypes.
A Blog post by Ai2 on Hugging Face
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.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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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