research

Reachability Constraints in Variational Quantum Circuits: Optimization within Polynomial Group Module

arXiv:2604.13735v1 Announce Type: cross Abstract: This work identifies a necessary condition for any variational quantum approach to reach the exact ground state. Briefly, the norms of the projections

Research

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

DGX agent

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

researcharxiv-cs-cv

16 Apr 2026

ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks

arXiv:2603.28942v3 Announce Type: replace Abstract: The pervasive deployment of deep learning models across critical domains has concurrently intensified privacy concerns due to their inherent propens

Right Regions, Wrong Labels: Semantic Label Flips in Segmentation under Correlation Shift

arXiv:2604.13326v1 Announce Type: new Abstract: The robustness of machine learning models can be compromised by spurious correlations between non-causal features in the input data and target labels. A

RobotPan: A 360^irc Surround-View Robotic Vision System for Embodied Perception

arXiv:2604.13476v1 Announce Type: cross Abstract: Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as tele

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate

arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces

Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model

arXiv:2510.18165v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) are emerging as a powerful and promising alternative to the dominant autoregressive paradigm, offering inhere

Scalable unsupervised feature selection via weight stability

arXiv:2506.06114v4 Announce Type: replace Abstract: Unsupervised feature selection is critical for improving clustering performance in high-dimensional data, where irrelevant features can obscure mean

Scale-Invariant Sampling in Multi-Arm Bandit Motion Planning for Object Extraction

arXiv:2604.14026v1 Announce Type: new Abstract: Object extraction tasks often occur in disassembly problems, where bolts, screws, or pins have to be removed from tight, narrow spaces. In such problems

SceneGlue: Scene-Aware Transformer for Feature Matching without Scene-Level Annotation

arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained

SEDTalker: Emotion-Aware 3D Facial Animation Using Frame-Level Speech Emotion Diarization

arXiv:2604.13335v1 Announce Type: new Abstract: We introduce SEDTalker, an emotion-aware framework for speech-driven 3D facial animation that leverages frame-level speech emotion diarization to achiev

Sign up today @ http://portal.nousresearch.com/manage-subscription Run `hermes update` and then `hermes model` to configure

Nous Research is promoting their subscription portal and providing instructions for users to update and configure their Hermes model through command-line tools (`hermes update` and `hermes model`). Th

researchnous-research--x

SiLVR: A Simple Language-based Video Reasoning Framework

arXiv:2505.24869v3 Announce Type: replace Abstract: Recent advances in test-time optimization have led to remarkable reasoning capabilities in Large Language Models (LLMs), enabling them to solve high

Simulation-Based Optimisation of Batting Order and Bowling Plans in T20 Cricket

arXiv:2604.13861v1 Announce Type: new Abstract: This paper develops a unified Markov Decision Process (MDP) framework for optimising two recurring in-match decisions in T20 cricket namely batting orde

Singularity Avoidance in Inverse Kinematics: A Unified Treatment of Classical and Learning-based Methods

arXiv:2604.13405v1 Announce Type: new Abstract: Singular configurations cause loss of task-space mobility, unbounded joint velocities, and solver divergence in inverse kinematics (IK) for serial manip

Social media polarization during conflict: Insights from an ideological stance dataset on Israel-Palestine Reddit comments

arXiv:2502.00414v2 Announce Type: replace Abstract: In politically sensitive scenarios like wars, social media serves as a platform for polarized discourse and expressions of strong ideological stance

Some Theoretical Limitations of t-SNE

arXiv:2604.13295v1 Announce Type: new Abstract: t-SNE has gained popularity as a dimension reduction technique, especially for visualizing data. It is well-known that all dimension reduction technique

Sparse or Dense? A Mechanistic Estimation of Computation Density in Transformer-based LLMs

arXiv:2601.22795v2 Announce Type: replace Abstract: Transformer-based large language models (LLMs) are comprised of billions of parameters arranged in deep and wide computational graphs. Several studi

SSD-GS: Scattering and Shadow Decomposition for Relightable 3D Gaussian Splatting

arXiv:2604.13333v1 Announce Type: new Abstract: We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photore

Stability Principle Underlying Passive Dynamic Walking of Rimless Wheel

arXiv:2604.13530v1 Announce Type: new Abstract: Rimless wheels are known as the simplest model for passive dynamic walking. It is known that the passive gait generated only by gravity effect always be

Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems

arXiv:2604.13297v1 Announce Type: cross Abstract: This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and sta

Swap Regret Minimization Through Response-Based Approachability

arXiv:2602.06264v2 Announce Type: replace Abstract: We consider the problem of minimizing different notions of swap regret in online optimization. These forms of regret are tightly connected to correl

The Download: cyberscammers’ banking bypasses, and carbon removal troubles

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. Cyberscammers are bypassing banks’ security with illicit tools

researchmit-tech-review

The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems

arXiv:2505.12836v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions comm

The quest to measure our relationship with nature

As a movement, environmentalism has been pretty misanthropic. Understandably so—we humans have done some destructive things to the ecosystems around us. In the 21st century, though, mainstream conserv

researchmit-tech-review

The Signal is in the Steps: Local Scoring for Reasoning Data Selection

arXiv:2510.03988v2 Announce Type: replace Abstract: Distilling long-form reasoning from teacher models into smaller students requires selecting which candidate solutions to train on. Recent work argue

The Spectrascapes Dataset: Street-view imagery beyond the visible captured using a mobile platform

arXiv:2604.13315v1 Announce Type: new Abstract: High-resolution data in spatial and temporal contexts is imperative for developing climate resilient cities. Current datasets for monitoring urban param

There's a broadly held misconception in AI that methods that scale well are simple methods -- even, that simple methods usually scale. This …

researchfrancois-chollet--x

There's a broadly held misconception in AI that methods that scale well are simple methods -- even, that simple methods usually scale. This is completely wrong. Pretty much none of the truly simple me

Tool Gateway is now live in Nous Portal. No separate accounts, no API key juggling. All you need is one subscription, and everything works. …

Tool Gateway is now live in Nous Portal. No separate accounts, no API key juggling. All you need is one subscription, and everything works. A paid Nous Portal subscription now includes access to 300+

researchnous-research--x

Towards Patient-Specific Deformable Registration in Laparoscopic Surgery

arXiv:2604.13186v1 Announce Type: new Abstract: Unsafe surgical care is a critical health concern, often linked to limitations in surgeon experience, skills, and situational awareness. Integrating pat

Towards Unconstrained Human-Object Interaction

arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations

arXiv:2601.07422v2 Announce Type: replace Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal stat

UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing

arXiv:2604.13565v1 Announce Type: new Abstract: Ultra-high-resolution (UHR) remote sensing imagery couples kilometer-scale context with query-critical evidence that may occupy only a few pixels. Such

Universality of Gaussian-Mixture Reverse Kernels in Conditional Diffusion

arXiv:2604.13470v1 Announce Type: new Abstract: We prove that conditional diffusion models whose reverse kernels are finite Gaussian mixtures with ReLU-network logits can approximate suitably regular

Using reasoning LLMs to extract SDOH events from clinical notes

arXiv:2604.13502v1 Announce Type: new Abstract: Social Determinants of Health (SDOH) refer to environmental, behavioral, and social conditions that influence how individuals live, work, and age. SDOH

Utilizing Inpainting for Keypoint Detection for Vision-Based Control of Robotic Manipulators

arXiv:2604.13309v1 Announce Type: new Abstract: In this paper we present a novel visual servoing framework to control a robotic manipulator in the configuration space by using purely natural visual fe

VibeFlow: Versatile Video Chroma-Lux Editing through Self-Supervised Learning

arXiv:2604.13425v1 Announce Type: new Abstract: Video chroma-lux editing, which aims to modify illumination and color while preserving structural and temporal fidelity, remains a significant challenge

VIGILant: an automatic classification pipeline for glitches in the Virgo detector

arXiv:2604.13687v1 Announce Type: cross Abstract: Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work in

Viktor Orbán’s electoral loss in Hungary is as much a defeat for Trump and JD Vance. 'Seldom have American leaders intervened so overtly in …

Viktor Orbán’s electoral loss in Hungary is as much a defeat for Trump and JD Vance. 'Seldom have American leaders intervened so overtly in a foreign election, and seldom has their preferred candidate

researchyann-lecun--x

Visual Sparse Steering (VS2): Unsupervised Adaptation for Image Classification using Sparsity-Guided Steering Vectors

arXiv:2506.01247v2 Announce Type: replace Abstract: Steering vision foundation models at test time, without updating foundation-model weights or using labeled target data, is a desirable yet challengi

VLMs Need Words: Vision Language Models Ignore Visual Detail In Favor of Semantic Anchors

arXiv:2604.02486v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have achieved impressive performance across a wide range of multimodal tasks. However, they often fail on tasks

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework

arXiv:2604.13438v1 Announce Type: new Abstract: Privacy concerns in LLMs have led to the rapidly growing need to enforce a data's 'right to be forgotten'. Machine unlearning addresses precisely this t

YOCO++: Enhancing YOCO with KV Residual Connections for Efficient LLM Inference

arXiv:2604.13556v1 Announce Type: new Abstract: Cross-layer key-value (KV) compression has been found to be effective in efficient inference of large language models (LLMs). Although they reduce the m

Zero-Shot Function Encoder-Based Differentiable Predictive Control

arXiv:2511.05757v3 Announce Type: replace-cross Abstract: We introduce a differentiable framework for zero-shot adaptive control over parametric families of nonlinear dynamical systems. Our approach i

3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope

arXiv:2604.12027v1 Announce Type: new Abstract: Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg informat

15 Apr 2026

A Bayesian Perspective on the Role of Epistemic Uncertainty for Delayed Generalization in In-Context Learning

arXiv:2604.12434v1 Announce Type: cross Abstract: In-context learning enables transformers to adapt to new tasks from a few examples at inference time, while grokking highlights that this generalizati

15 Apr 2026

A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting

arXiv:2603.10559v2 Announce Type: replace Abstract: This paper studies cross-market return predictability through a machine learning framework that preserves economic structure. Exploiting the non-ove