research

SeDeM: Selective Decompression of Hidden-State Memories for Long-Context Question Answering

arXiv:2608.00311v1 Announce Type: new Abstract: Long-context inference with large language models (LLMs) is costly: self-attention during prefill scales quadratically with sequence length, and the key

Research

Seeing the Unseen: Towards Training-Free Inspection for Wind Turbine Blades Using Knowledge-Augmented Vision Language Models

DGX agent

arXiv:2510.22868v2 Announce Type: replace Abstract: Wind turbine blades operate in harsh environments, making timely damage detection essential for preventing failures and optimizing maintenance. Dron

researcharxiv-cs-cv

4 Aug 2026

Select-And-Extract: A Lightweight Plugin for Retrieval-Augmented Generation

arXiv:2608.00658v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) for language model (LM) systems fundamentally has two failure modes: retrieval failure and reading failure. The for

Self-supervised DXA representations encode multi-system disease risk, biological aging and heritability

arXiv:2608.02208v1 Announce Type: new Abstract: Whole-body dual-energy X-ray absorptiometry (DXA) scans are routinely acquired to measure bone density and regional body composition, leaving their spat

Self-Supervised Representations for Binary Program Clustering: From Empirical Study to Retrieval-Augmented Learning

arXiv:2608.02348v1 Announce Type: cross Abstract: Malware clustering is a critical task in cybersecurity that helps discover threats and analyze evolving malware families. While self-supervised learni

Sheaf-theoretic Signal Processing on Graphs: Spectral Theory, Filtering, and Sampling

arXiv:2608.01318v1 Announce Type: cross Abstract: Modern sensing, communication, and learning systems generate heterogeneous network signals, with local data differing in dimension, modality, and geom

Similarity Weighted Aggregation with Global Differential Privacy for Federated Brain Lesion Segmentation

arXiv:2608.00872v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative training of machine learning models across multiple institutions without sharing sensitive data, making

Simplified Quadratic Gradient: A Unified Framework Bridging Gradient Descent and Newton-Type Methods by Synthesizing Hessians and Gradients

arXiv:2209.03282v5 Announce Type: replace-cross Abstract: Accelerating the convergence of second-order optimization, particularly Newton-type methods, remains a pivotal challenge in algorithmic resear

Sixteen models, fewer than two voices: measuring ensemble dispersion where no answer is uniquely correct

arXiv:2608.00285v1 Announce Type: new Abstract: Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic case,

Smooth Reparameterizations of Functions on Simplicial Product Spaces: Applications to Probabilistic Tensor Decomposition and Functional Data Registration

arXiv:2608.02576v1 Announce Type: new Abstract: We consider optimization problems defined on product spaces of simplices. Examples of this class of problems include learning low-rank discrete multivar

Sparse Covariance Neural Networks

arXiv:2410.01669v3 Announce Type: replace Abstract: Covariance Neural Networks (VNNs) perform graph convolutions on the covariance matrix of input data to leverage correlation information as pairwise

Sparse Meets Dense: Correspondence Guided Robotic Manipulation with Rigid-Deformable Interactions

arXiv:2608.01083v1 Announce Type: new Abstract: Manipulation involving rigid-deformable interactions, such as hanging clothes or dressing humans, is common in daily life, making it essential for house

SpikeRestormer: Towards Energy-Efficient All-in-One Image Restoration via Unified Event Reasoning

arXiv:2608.02290v1 Announce Type: new Abstract: ANN-based All-in-One image restoration (AiOIR) unifies diverse degradation handling but incurs high computational costs, limiting its real-time deployme

SSTG-Nav: Metric-Grounded Spatial-Semantic Topological Graphs for Reusable Object Navigation

arXiv:2608.00527v1 Announce Type: new Abstract: Service robots operating for months in the same homes, offices, and facilities should become more reliable with experience instead of searching familiar

Stabilized Best-of-K Training for Neural Combinatorial Optimization

arXiv:2608.00296v1 Announce Type: new Abstract: Leader Reward modifies POMO training to emphasize the best trajectory produced by repeated inference. We test a narrow extension: replace its binary lea

Statistical comparisons of time-series feature sets on classification tasks

arXiv:2608.01586v1 Announce Type: cross Abstract: In recent years, numerous open-source software libraries have been developed for computing sets of features from univariate time series. The type and

Statistical Mechanics of Learning on Product Wasserstein Manifolds

arXiv:2608.01434v1 Announce Type: new Abstract: Normally the statistical mechanics of learning treats constraints on weight distributions as restrictions that shrink the space of possible solutions. T

STC-Net: Electroluminescence-Based Solar Cell Crack Segmentation for Power Loss Estimation

arXiv:2608.01714v1 Announce Type: new Abstract: Accurate crack assessment in electroluminescence (EL) images is important for photovoltaic (PV) reliability analysis, yet existing segmentation methods

Stochastic Sequential Search in Very-High-Dimensional Feature Selection

arXiv:2608.01502v1 Announce Type: cross Abstract: Sequential subset search -- forward selection with floating backtracking and its descendants -- remains the quality reference in feature selection, bu

StreamSplat: Streaming Feed-Forward 3D Gaussian Splatting

arXiv:2608.01659v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting enables efficient novel-view synthesis without per-scene optimization, but most existing methods assume a fixed set o

StreamTalk: Streaming Co-Speech Gesture Generation with Key-Pose Anchoring

arXiv:2608.01643v1 Announce Type: new Abstract: Real-time co-speech gesture generation must produce 3D motion clip by clip as speech arrives. Existing streaming methods are open-loop: each clip depend

Subtype Robustness Is Not Just Accuracy: Calibration Under Unseen Subtype Shift

arXiv:2608.00928v1 Announce Type: new Abstract: Subtype robustness asks whether a model keeps the correct coarse prediction when test examples come from fine-grained subtypes absent from training but

Surrogate Modeling for the Design of Optimal Lattice Structures using Tensor Completion

arXiv:2510.07474v2 Announce Type: replace Abstract: When designing new materials, it is often necessary to design a material with specific desired properties. Unfortunately, as new design variables ar

Swimm3R: Splatting with Medium-aware SfM for Underwater 3D Reconstruction

arXiv:2608.00950v1 Announce Type: new Abstract: We propose Swimm3R, a unified framework that combines medium-aware structure-from-motion (SfM) with Underwater Beta Splatting to address scattering- and

SWINSleepNet: A Hierarchical Context-Aware Framework for Sleep Staging (v2)

arXiv:2608.02183v1 Announce Type: new Abstract: Automatic sleep staging is a critical role in sleep disorder diagnosis, sleep quality assessment, and long-term health monitoring; however, existing app

T-TAMER: Provably Taming Trade-offs in ML Serving

arXiv:2509.22992v2 Announce Type: replace Abstract: As machine learning models continue to grow in size and complexity, efficient serving faces increasingly broad trade-offs spanning accuracy, latency

Test-time Adaptation of Pelvic Bone Segmentation Models via Dynamic Reliability-Guided

arXiv:2608.00510v1 Announce Type: new Abstract: Reliable pelvic bone segmentation (PBS) from CT is essential for robot-assisted pelvic trauma surgery, yet deploying a source-trained model to a new hos

tFUSOperator: Operator Learning for Transcranial Focused Ultrasound Digital Twins

arXiv:2608.01839v1 Announce Type: new Abstract: Transcranial focused ultrasound (tFUS) requires accurate estimation of the intracranial acoustic field, which is distorted by skull-induced aberrations.

The Bayesian Reflex: A Predictive Coding Engine for Artificial Intelligence

arXiv:2608.00492v1 Announce Type: cross Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence

The Download: US robot restrictions, and ICE’s DNA grab

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Trump’s AI protectionism has come for robotics —James O’Donnel

researchmit-tech-review

The Elements of Differentiable Programming

arXiv:2403.14606v4 Announce Type: replace Abstract: Artificial intelligence has recently experienced remarkable advances, fueled by large models, vast datasets, accelerated hardware, and, last but not

The Fourth Quadrant: A Stylized View of Benign Misfitting

arXiv:2608.01032v1 Announce Type: new Abstract: Training error is what we can observe on a training set; test error is the quantity we actually care about. We study linear regression with squared-erro

The Gate, Not the Cache: Gate Provenance Bounds the Closed-Loop Reliability of Training-Free VLA Token Skipping

arXiv:2608.00391v1 Announce Type: new Abstract: Token skipping is a widely used training-free way to accelerate vision--language--action (VLA) models by bypassing computation for most visual tokens at

The Holistic Storage of Verb+Up Phrases in Text-based and Audio-based Language Models

arXiv:2606.13993v2 Announce Type: replace Abstract: A crucial aspect of linguistic capability is the ability to trade off between stored representations and abstract knowledge: one must retrieve learn

The Label Defines the Timescale: Trait-State Limits of Temporal-Aggregate Learning

arXiv:2608.01587v1 Announce Type: cross Abstract: Machine-learning benchmarks often pair a label that aggregates a long temporal horizon with input observed through one or a few short windows. Their a

The methodology of Constructing the Large-Scale Dataset for Detecting Presuicidal and Anti-Suicidal Signals in Social Media Texts in Russian

arXiv:2608.00497v1 Announce Type: new Abstract: The suicide is a terrifying act of a person who is misled by his own mental state. This problem arises across many countries. Sadly, Russia also has qui

The No-Clash Teaching Dimension is Bounded by VC Dimension

arXiv:2603.23561v4 Announce Type: replace-cross Abstract: In the realm of machine learning theory, to prevent unnatural coding schemes between teacher and learner, No-Clash Teaching Dimension was intr

Thermalizing Stochastic Programs

arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a

Think in Sets for Streaming Video Token Compression

arXiv:2608.01169v1 Announce Type: new Abstract: Streaming VideoLLMs process frames causally while visual tokens grow continuously, making compression essential for controlling prefilling latency and m

Token Radius Attention for Efficient Video Generation

arXiv:2608.02504v1 Announce Type: new Abstract: Video Diffusion Transformers (VDiTs) enable high-fidelity generation but incur quadratic cost from dense 3D self-attention. Existing head- and block-lev

Towards a theory of morphology-driven marking in the lexicon: The case of the state

arXiv:2604.03422v2 Announce Type: replace Abstract: All languages have a noun category, but its realisation varies considerably. Depending on the language, semantic and/or morphosyntactic differences

Towards Effective Federated Multimodal Graph Learning via Navigating Multifaceted Heterogeneity

arXiv:2608.00623v1 Announce Type: new Abstract: Multimodal-attributed graphs (MAGs), where nodes carry heterogeneous semantic content across multiple modalities while edges encode relational dependenc

TRACE: Ergodic Trajectory Optimization for Active Scene Reconstruction

arXiv:2608.02304v1 Announce Type: new Abstract: Existing active reconstruction systems with Gaussian-splatting maps select observations greedily, optimizing a single next-best-view (NBV) at each step

Training-Free Out-of-Distribution Detection for Pathology Whole-Slide Images

arXiv:2608.01407v1 Announce Type: new Abstract: Safe deployment of AI methods in medicine requires robust guardrails that detect when input data deviate from the training distribution to ensure that m

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes

arXiv:2608.02415v1 Announce Type: new Abstract: Intent classification in Large Language Models (LLMs) involves categorizing user prompts into predefined classes. For instance, given a user prompt, the

TRAM: Enhancing Multimodal Reasoning with Trajectory-Derived Auxiliary Memory

arXiv:2608.01922v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved strong performance on tasks requiring visual understanding and multi-step inference. However, as

Transformer Geometry Observatory TGO-III: Semantic Geometry Observatory

arXiv:2608.01876v1 Announce Type: new Abstract: With the widespread adoption of Vision Transformers in modern AI, the need to analyze their inherent representational behavior has become increasingly i

Transformers perform adaptive partial pooling

arXiv:2602.03980v2 Announce Type: replace Abstract: Any language model must decide what to say in novel contexts based on information from similar contexts. But what about contexts that are not novel