research

I scaled a pure Spiking Neural Network (SNN) to 1.088B parameters from scratch. Ran out of budget, but here is what I found [R]

A researcher on r/MachineLearning documented an independent attempt to scale a pure Spiking Neural Network (SNN) to 1.088 billion parameters, built from scratch, exploring whether SNNs can achieve per

Research

[ICML 2026] Extending the deadline for reviewer final justifications while not extending for Author-AC comments was a huge mistake [D]

DGX agent

A Reddit discussion thread on r/MachineLearning criticizing a procedural misstep in the ICML 2026 review process, where reviewers are newly required this year to provide a final justification describi

researchr-machinelearning

13 Apr 2026

[ICML 2026] Scores for Position papers post discussion? [D]

This r/MachineLearning discussion thread focuses on the post-discussion reviewer scores for ICML 2026's dedicated Position Paper Track, where authors and community members share and compare their revi

Identifying Causal Effects Using a Single Proxy Variable

arXiv:2604.09135v1 Announce Type: cross Abstract: Unobserved confounding is a key challenge when estimating causal effects from a treatment on an outcome in scientific applications. In this work, we a

IKKA: Inversion Classification via Critical Anomalies for Robust Visual Servoing

arXiv:2604.08754v1 Announce Type: new Abstract: We introduce IKKA (Inversion Classification via Critical Anomalies), a topologically motivated weighting framework for robust visual servoing under dist

'I'm just contemplating the fact that one moron, one psychotic moron, one capricious idiot, has completely bollocksed up the global economy …

'I'm just contemplating the fact that one moron, one psychotic moron, one capricious idiot, has completely bollocksed up the global economy not only to the detriment of his own people, but the detrime

researchyann-lecun--x

Imitation Learning for Combinatorial Optimisation under Uncertainty

arXiv:2601.05383v4 Announce Type: replace Abstract: Imitation learning (IL) provides a data-driven framework for approximating policies for large-scale combinatorial optimisation problems formulated a

Implementation details of Backpropagation in Siamese networks. [D]

This Reddit discussion on r/MachineLearning explores the practical implementation details of backpropagation in Siamese networks, which consist of two or more identical subnetworks with shared weights

Incremental Semantics-Aided Meshing from LiDAR-Inertial Odometry and RGB Direct Label Transfer

arXiv:2604.09478v1 Announce Type: new Abstract: Geometric high-fidelity mesh reconstruction from LiDAR-inertial scans remains challenging in large, complex indoor environments -- such as cultural buil

InsEdit: Towards Instruction-based Visual Editing via Data-Efficient Video Diffusion Models Adaptation

arXiv:2604.08646v1 Announce Type: new Abstract: Instruction-based video editing is a natural way to control video content with text, but adapting a video generation model into an editor usually appear

Integrated electro-optic attention nonlinearities for transformers

arXiv:2604.09512v1 Announce Type: new Abstract: Transformers have emerged as the dominant neural-network architecture, achieving state-of-the-art performance in language processing and computer vision

Interactive Program Synthesis for Modeling Collaborative Physical Activities from Narrated Demonstrations

arXiv:2509.24250v3 Announce Type: replace Abstract: Teaching systems physical tasks is a long standing goal in HCI, yet most prior work has focused on non collaborative physical activities. Collaborat

Intrinsic Concept Extraction Based on Compositional Interpretability

arXiv:2603.11795v2 Announce Type: replace Abstract: Unsupervised Concept Extraction aims to extract concepts from a single image; however, existing methods suffer from the inability to extract composa

Is More Data Worth the Cost? Dataset Scaling Laws in a Tiny Attention-Only Decoder

arXiv:2604.09389v1 Announce Type: cross Abstract: Training Transformer language models is expensive, as performance typically improves with increasing dataset size and computational budget. Although s

Iterative Identification Closure: Amplifying Causal Identifiability in Linear SEMs

arXiv:2604.09309v1 Announce Type: cross Abstract: The Half-Trek Criterion (HTC) is the primary graphical tool for determining generic identifiability of causal effect coefficients in linear structural

Job titles of the future: Wildlife first responder

Grizzly bears have made such a comeback across eastern Montana that in 2017, the state hired its first-ever prairie-based grizzly manager: wildlife biologist Wesley Sarmento. For some seven years, Sar

researchmit-tech-review

Joint Interference Detection and Identification via Adversarial Multi-task Learning

arXiv:2604.08607v1 Announce Type: cross Abstract: Precise interference detection and identification are crucial for enhancing the survivability of communication systems in non-cooperative wireless env

Just like us at @thinkymachines, @luke_drago_ @LRudL_ care a lot about amplifying humans, not replacing them. They're joining us to build to…

researchsoumith-chintala--x

Just like us at @thinkymachines, @luke_drago_ @LRudL_ care a lot about amplifying humans, not replacing them. They're joining us to build towards that future! Workshop Labs is joining @thinkymachines.

Large-Scale Universal Defect Generation: Foundation Models and Datasets

arXiv:2604.08915v1 Announce Type: cross Abstract: Existing defect/anomaly generation methods often rely on few-shot learning, which overfits to specific defect categories due to the lack of large-scal

Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction

arXiv:2506.11552v2 Announce Type: replace-cross Abstract: Quantum error correction is crucial for protecting quantum information against decoherence. Traditional codes like the surface code require su

LLM Dictionary: A reference to contemporary LLM vocabulary [P]

This Reddit post on r/MachineLearning presents a community-contributed dictionary of contemporary Large Language Model (LLM) terminology, covering terms related to training, fine-tuning, inference, al

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation

arXiv:2510.23636v3 Announce Type: replace-cross Abstract: Flight delay prediction has become a key focus in air traffic management (ATM), as delays reflect inefficiencies in the system. This paper pro

LLMs Underperform Graph-Based Parsers on Supervised Relation Extraction for Complex Graphs

arXiv:2604.08752v1 Announce Type: cross Abstract: Relation extraction represents a fundamental component in the process of creating knowledge graphs, among other applications. Large language models (L

LoBE-GS: Load-Balanced and Efficient 3D Gaussian Splatting for Large-Scale Scene Reconstruction

arXiv:2510.01767v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has established itself as an efficient representation for real-time, high-fidelity 3D scene reconstruction. However, sc

Localizing Task Recognition and Task Learning in In-Context Learning via Attention Head Analysis

arXiv:2509.24164v2 Announce Type: replace Abstract: We investigate the mechanistic underpinnings of in-context learning (ICL) in large language models by reconciling two dominant perspectives: the com

Loom: A Scalable Analytical Neural Computer Architecture

arXiv:2604.08816v1 Announce Type: new Abstract: We present Loom, a computer architecture that executes programs compiled from C inside a looped transformer whose weights are derived analytically. The

Mandatory In-Person Presentation in CVPR 2026 [D]

This Reddit thread on r/MachineLearning discusses CVPR 2026's policy requiring accepted papers to be registered under an in-person author registration, with virtual attendance still permitted if circu

MASS: Mesh-inellipse Aligned Deformable Surfel Splatting for Hand Reconstruction and Rendering from Egocentric Monocular Video

arXiv:2604.08943v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D hands from egocentric monocular videos remains a challenge due to the limitations in capturing high-resolution geometry,

Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers

arXiv:2601.04791v3 Announce Type: replace Abstract: While latent diffusion models (LDMs) have emerged as powerful priors for inverse problems, existing LDM-based solvers frequently suffer from instabi

Meta-Learned Basis Adaptation for Parametric Linear PDEs

arXiv:2604.09289v1 Announce Type: new Abstract: We propose a hybrid physics-informed framework for solving families of parametric linear partial differential equations (PDEs) by combining a meta-learn

Modality-Aware Zero-Shot Pruning and Sparse Attention for Efficient Multimodal Edge Inference

arXiv:2604.08971v1 Announce Type: new Abstract: Edge devices increasingly run multimodal sensing pipelines that must remain accurate despite fluctuating power budgets and unpredictable sensor dropout.

Multi-task Just Recognizable Difference for Video Coding for Machines: Database, Model, and Coding Application

arXiv:2604.09421v1 Announce Type: cross Abstract: Just Recognizable Difference (JRD) boosts coding efficiency for machine vision through visibility threshold modeling, but is currently limited to a si

Music Audio-Visual Question Answering Requires Specialized Multimodal Designs

arXiv:2505.20638v2 Announce Type: replace-cross Abstract: While recent Multimodal Large Language Models exhibit impressive capabilities for general multimodal tasks, specialized domains like music nec

[N] AMA Announcement: Max Welling (VAEs, GNNs, AI4Science & CuspAI)

This r/MachineLearning AMA announcement features Max Welling, a prominent figure in machine learning renowned for his foundational contributions to probabilistic deep learning, including the co-develo

Nested Radially Monotone Polar Occupancy Estimation: Clinically-Grounded Optic Disc and Cup Segmentation for Glaucoma Screening

arXiv:2604.09062v1 Announce Type: new Abstract: Valid segmentation of the optic disc (OD) and optic cup (OC) from fundus photographs is essential for glaucoma screening. Unfortunately, existing deep l

一つのニューラルネットに符号と記号は創発しうるか？「Neural Computers」論文から考える @rmaruy https://rmaruy.hatenablog.com/entry/2026/04/11/223828

This Japanese blog post explores whether signs and symbols can emerge within a single neural network, drawing on analysis of the 'Neural Computers' paper. The discussion likely examines the intersecti

researchdavid-ha--x

No Single Best Model for Diversity: Learning a Router for Sample Diversity

arXiv:2604.02319v2 Announce Type: replace Abstract: When posed with prompts that permit a large number of valid answers, comprehensively generating them is the first step towards satisfying a wide ran

OASIS: Online Activation Subspace Learning for Memory-Efficient Training

arXiv:2604.09406v1 Announce Type: new Abstract: Training large language models (LLMs) is constrained by memory requirements, with activations accounting for a substantial fraction of the total footpri

Offline Local Search for Online Stochastic Bandits

arXiv:2604.09423v1 Announce Type: new Abstract: Combinatorial multi-armed bandits provide a fundamental online decision-making environment where a decision-maker interacts with an environment across T

On the Limits of Layer Pruning for Generative Reasoning in Large Language Models

arXiv:2602.01997v2 Announce Type: replace-cross Abstract: Recent work has shown that layer pruning can effectively compress large language models (LLMs) while retaining strong performance on classific

On the Terminology and Geometric Aspects of Redundant Parallel Manipulators

arXiv:2604.09156v1 Announce Type: new Abstract: Parallel kinematics machines (PKM) can exhibit kinematic as well as actuation redundancy. While the meaning of kinematic redundancy has been clarified a

researcharxiv-cs-ro

One Interface, Many Robots: Unified Real-Time Low-Level Motion Planning for Collaborative Arms

arXiv:2604.08787v1 Announce Type: new Abstract: This paper proposes a common interface for real-time low-level motion planning of collaborative robotic arms, aimed at enabling broader applicability an

researcharxiv-cs-ro

Online Quantile Regression for Nonparametric Additive Models

arXiv:2604.08969v1 Announce Type: cross Abstract: This paper introduces a projected functional gradient descent algorithm (P-FGD) for training nonparametric additive quantile regression models in onli

Optimal Multi-bit Generative Watermarking Schemes Under Worst-Case False-Alarm Constraints

arXiv:2604.08759v1 Announce Type: cross Abstract: This paper considers the problem of multi-bit generative watermarking for large language models under a worst-case false-alarm constraint. Prior work

Out-of-the-box: Black-box Causal Attacks on Object Detectors

arXiv:2512.03730v2 Announce Type: replace-cross Abstract: Adversarial perturbations are a useful way to expose vulnerabilities in object detectors. Existing perturbation methods are frequently white-b

Overhang Tower: Resource-Rational Adaptation in Sequential Physical Planning

arXiv:2604.09072v1 Announce Type: new Abstract: Humans effortlessly navigate the physical world by predicting how objects behave under gravity and contact forces, yet how such judgments support sequen

Overstating Attitudes, Ignoring Networks: LLM Biases in Simulating Misinformation Susceptibility

arXiv:2602.04674v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reprodu

p1: Better Prompt Optimization with Fewer Prompts

arXiv:2604.08801v1 Announce Type: cross Abstract: Prompt optimization improves language models without updating their weights by searching for a better system prompt, but its effectiveness varies wide