Search: “research”

Reservoir observer enhanced with residual calibration and attention mechanism

arXiv:2604.08592v1 Announce Type: new Abstract: Reservoir observers provide a data-driven approach to the inference of unmeasured variables from observed ones for nonlinear dynamical systems. While pr

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Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective

DGX agent

arXiv:2604.08880v1 Announce Type: cross Abstract: Chain-of-thought (CoT) distillation transfers reasoning behaviors from a strong teacher to a smaller student, but prior work reports a capacity gap: d

researcharxiv-cs-ai

13 Apr 2026

Sample Complexity of Composite Quantum Hypothesis Testing

arXiv:2601.08588v4 Announce Type: replace-cross Abstract: This paper investigates symmetric composite binary quantum hypothesis testing (QHT), where the goal is to determine which of two uncertainty s

Scaling flow-based approaches for topology sampling in SU(3) gauge theory

arXiv:2510.25704v2 Announce Type: replace-cross Abstract: We develop a methodology based on out-of-equilibrium simulations to mitigate topological freezing when approaching the continuum limit of latt

Safety

Scheming in the wild: detecting real-world AI scheming incidents with open-source intelligence

arXiv:2604.09104v1 Announce Type: cross Abstract: Scheming, the covert pursuit of misaligned goals by AI systems, represents a potentially catastrophic risk, yet scheming research suffers from signifi

safetyarxiv-cs-ai

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

arXiv:2601.22160v2 Announce Type: replace-cross Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies

Self-Supervised Slice-to-Volume Reconstruction with Gaussian Representations for Fetal MRI

arXiv:2601.22990v2 Announce Type: replace-cross Abstract: Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume r

Sharp description of local minima in the loss landscape of high-dimensional two-layer ReLU neural networks

arXiv:2604.09412v1 Announce Type: cross Abstract: We study the population loss landscape of two-layer ReLU networks of the form sum_{k=1}^K ReLU(w_k^op x) in a realisable teacher-student setting with

SIC3D: Style Image Conditioned Text-to-3D Gaussian Splatting Generation

arXiv:2604.08760v1 Announce Type: new Abstract: Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differe

Silhouette Loss: Differentiable Global Structure Learning for Deep Representations

arXiv:2604.08573v1 Announce Type: cross Abstract: Learning discriminative representations is a central goal of supervised deep learning. While cross-entropy (CE) remains the dominant objective for cla

Simulation of Adaptive Running with Flexible Sports Prosthesis using Reinforcement Learning of Hybrid-link System

arXiv:2604.08882v1 Announce Type: new Abstract: This study proposes a reinforcement learning-based adaptive running motion simulation for a unilateral transtibial amputee with the flexibility of a lea

researcharxiv-cs-ro

Soft Electroadhesive Feet for Micro Aerial Robots Perching on Smooth and Curved Surfaces

arXiv:2604.09270v1 Announce Type: new Abstract: Electroadhesion (EA) provides electrically switchable adhesion and is a promising mechanism for perching micro aerial robots on smooth surfaces. However

researcharxiv-cs-ro

State Space Models are Effective Sign Language Learners: Exploiting Phonological Compositionality for Vocabulary-Scale Recognition

arXiv:2604.08761v1 Announce Type: new Abstract: Sign language recognition suffers from catastrophic scaling failure: models achieving high accuracy on small vocabularies collapse at realistic sizes. E

Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains

arXiv:2604.09361v1 Announce Type: new Abstract: In this paper, we propose a stochastic-dimension frozen sampled neural network (SD-FSNN) for solving a class of high-dimensional Gross-Pitaevskii equati

Streaming Video Instruction Tuning

arXiv:2512.21334v2 Announce Type: replace Abstract: We present Streamo, a real-time streaming video LLM that serves as a general-purpose interactive assistant. Unlike existing online video models that

Strips as Tokens: Artist Mesh Generation with Native UV Segmentation

arXiv:2604.09132v1 Announce Type: new Abstract: Recent advancements in autoregressive transformers have demonstrated remarkable potential for generating artist-quality meshes. However, the token order

Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis

arXiv:2604.08809v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) represent visual content as structured, editable code. Each element (path, shape, or text node) can be individually inspe

Structure-Aware Fine-Grained Gaussian Splatting for Expressive Avatar Reconstruction

arXiv:2604.09324v1 Announce Type: new Abstract: Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision an

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions

arXiv:2604.08477v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has significantly improved large language model (LLM) reasoning in formal domains such as mathem

Task-Aware LLM Routing with Multi-Level Task-Profile-Guided Data Synthesis for Cold-Start Scenarios

arXiv:2604.09377v1 Announce Type: new Abstract: Large language models (LLMs) exhibit substantial variability in performance and computational cost across tasks and queries, motivating routing systems

Task Vectors, Learned Not Extracted: Performance Gains and Mechanistic Insight

arXiv:2509.24169v2 Announce Type: replace Abstract: Large Language Models (LLMs) can perform new tasks from in-context demonstrations, a phenomenon known as in-context learning (ICL). Recent work sugg

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy

arXiv:2312.09436v3 Announce Type: replace-cross Abstract: The recent development of connected and automated vehicle (CAV) technologies has spurred investigations to optimize dense urban traffic to max

Testing the Assumptions of Active Learning for Translation Tasks with Few Samples

arXiv:2604.08977v1 Announce Type: new Abstract: Active learning (AL) is a training paradigm for selecting unlabeled samples for annotation to improve model performance on a test set, which is useful w

The Download: how humans make decisions, and Moderna’s “vaccine” word games

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. You have no choice in reading this article—maybe How do humans

researchmit-tech-review

The Fast Lane Hypothesis: Von Economo Neurons Implement a Biological Speed-Accuracy Tradeoff

arXiv:2604.09229v1 Announce Type: cross Abstract: Von Economo neurons (VENs) are large bipolar projection neurons found exclusively in the anterior cingulate cortex (ACC) and frontal insula of species

The Impact of Gait Pattern Personalization on the Perception of Rigid Robotic Guidance: A Pilot User Experience Evaluation

arXiv:2512.17425v2 Announce Type: replace Abstract: Exoskeletons modulate human movement across diverse applications, from performance augmentation to daily-life assistance. These systems often enforc

researcharxiv-cs-ro

The poisonous atmosphere around AI innovation is caused by a lethal combo: 1) idiotic messaging from AI execs (it will take your job) 2) doo…

The poisonous atmosphere around AI innovation is caused by a lethal combo: 1) idiotic messaging from AI execs (it will take your job) 2) doomers inciting violence and warning of the end of all life 3)

researchyann-lecun--x

Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models

arXiv:2603.01400v2 Announce Type: replace Abstract: Video Large Language Models (VLLMs) demonstrate strong video understanding but suffer from inefficiency due to redundant visual tokens. Existing pru

TopoFlow: Topography-aware Pollutant Flow Learning for High-Resolution Air Quality Prediction

arXiv:2602.16821v2 Announce Type: replace Abstract: We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality predictio

Tracing the Chain: Deep Learning for Stepping-Stone Intrusion Detection

arXiv:2604.08800v1 Announce Type: cross Abstract: Stepping-stone intrusions (SSIs) are a prevalent network evasion technique in which attackers route sessions through chains of compromised intermediat

Trained a Qwen2.5-0.5B-Instruct bf16 model on Reddit post summarization task with GRPO [P]

researchr-machinelearning

A community practitioner post on r/MachineLearning documenting an experiment fine-tuning Alibaba's Qwen2.5-0.5B-Instruct model in bf16 precision on a Reddit post summarization task using GRPO (Group R

Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory

arXiv:2604.09320v1 Announce Type: cross Abstract: Mechanistic understanding and rational design of complex chemical systems depend on fast and accurate predictions of electronic structures beyond indi

UHD Low-Light Image Enhancement via Real-Time Enhancement Methods with Clifford Information Fusion

arXiv:2604.09321v1 Announce Type: cross Abstract: Considering efficiency, ultra-high-definition (UHD) low-light image restoration is extremely challenging. Existing methods based on Transformer archit

UIPress: Bringing Optical Token Compression to UI-to-Code Generation

arXiv:2604.09442v1 Announce Type: new Abstract: UI-to-Code generation requires vision-language models (VLMs) to produce thousands of tokens of structured HTML/CSS from a single screenshot, making visu

Uncertainty-Aware Transformers: Conformal Prediction for Language Models

arXiv:2604.08885v1 Announce Type: new Abstract: Transformers have had a profound impact on the field of artificial intelligence, especially on large language models and their variants. However, as was

Universal Approximation with XL MIMO Systems: OTA Classification via Trainable Analog Combining

arXiv:2504.12758v3 Announce Type: replace-cross Abstract: In this paper, we show that an eXtremely Large (XL) Multiple-Input Multiple-Output (MIMO) wireless system with appropriate analog combining co

Unmasking Puppeteers: Leveraging Biometric Leakage to Disarm Impersonation in AI-based Videoconferencing

arXiv:2510.03548v3 Announce Type: replace-cross Abstract: AI-based talking-head videoconferencing systems reduce bandwidth by sending a compact pose-expression latent and re-synthesizing RGB at the re

Using Synthetic Data for Machine Learning-based Childhood Vaccination Prediction in Narok, Kenya

arXiv:2604.08902v1 Announce Type: new Abstract: Background: Limited data utilization in low-resource settings poses a barrier to the vaccine delivery ecosystem, undermining efforts to achieve equitabl

Variational Quantum Physics-Informed Neural Networks for Hydrological PDE-Constrained Learning with Inherent Uncertainty Quantification

arXiv:2604.09374v1 Announce Type: cross Abstract: We propose a Hybrid Quantum-Classical Physics-Informed Neural Network (HQC-PINN) that integrates parameterized variational quantum circuits into the P

VisionFoundry: Teaching VLMs Visual Perception with Synthetic Images

arXiv:2604.09531v1 Announce Type: cross Abstract: Vision-language models (VLMs) still struggle with visual perception tasks such as spatial understanding and viewpoint recognition. One plausible contr

VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning

arXiv:2604.09529v1 Announce Type: cross Abstract: Large Vision Language Models (LVLMs) achieve strong multimodal reasoning but frequently exhibit hallucinations and incorrect responses with high certa

VSI: Visual Subtitle Integration for Keyframe Selection to enhance Long Video Understanding

arXiv:2508.06869v4 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) demonstrate exceptional performance in vision-language tasks, yet their processing of long videos is

WAND: Windowed Attention and Knowledge Distillation for Efficient Autoregressive Text-to-Speech Models

arXiv:2604.08558v1 Announce Type: cross Abstract: Recent decoder-only autoregressive text-to-speech (AR-TTS) models produce high-fidelity speech, but their memory and compute costs scale quadratically

Want to understand the current state of AI? Check out these charts.

If you’re following AI news, you’re probably getting whiplash. AI is a gold rush. AI is a bubble. AI is taking your job. AI can’t even read a clock. The 2026 AI Index from Stanford University’s Instit

researchmit-tech-review

Weak Adversarial Neural Pushforward Method for the Wigner Transport Equation

arXiv:2604.08763v1 Announce Type: cross Abstract: We extend the Weak Adversarial Neural Pushforward Method to the Wigner transport equation governing the phase-space dynamics of quantum systems. The c

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

arXiv:2510.06499v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable success through imitation learning on vast text corpora, but this paradigm creates a tra

Which conference/journal do you believe currently has the most fair and accurate review process?[D]

researchr-machinelearning

This r/MachineLearning discussion thread invites community members to share their opinions on which ML conferences or journals they consider to have the fairest and most accurate peer review processes