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tutorialsr-machinelearning

Hey everyone! I am trying to go really deep into Machine Learning and Artificial Intelligence. Not just learning how to use the latest models and frameworks, but understanding how we reached here from

ResOPD: Tail Residualization for Sparse On-Policy Distillation

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arXiv:2610.04882v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model on self-generated trajectories, but transmitting dense teacher distributions across long reasoning t

safetyarxiv-cs-lg

6 Oct 2026

Hardware

Rethinking Least-Core Computation in Contextual-Distractor Games

arXiv:2610.06087v1 Announce Type: new Abstract: Game-theoretic attribution explains a model by assigning credit to its features or training examples. The least core has attracted interest as an altern

hardwarearxiv-cs-lg

RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation

Training a single LLM agent jointly across diverse interactive environments has attracted increasing attention as a route to generalist agents. Existing curriculum and data-selection strategies often

agentsapple-ml-research

SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

arXiv:2610.04109v1 Announce Type: new Abstract: Real-world time series are frequently driven by exogenous events and structural shifts, rendering conventional forecasting based solely on historical nu

safetyarxiv-cs-lg

SoundWeaver: Compositional Warm-Starting for Text-to-Audio Diffusion Serving

arXiv:2603.07865v2 Announce Type: replace-cross Abstract: Text-to-audio (T2A) diffusion models generate high-quality audio but require tens of neural function evaluations (NFEs), resulting in substant

StepCAD: Mesh-to-CAD Code Generation via LLM Policy and Geometry-Guided Search

arXiv:2610.03799v1 Announce Type: new Abstract: Recovering executable CAD programs from 3D meshes is challenging due to the compositional nature of CAD construction and the interaction between discret

T-JEPA: A Temporal Joint-Embedding Predictive Architecture for Learning Better Remote Sensing Representations

arXiv:2610.05731v1 Announce Type: new Abstract: Earth observation (EO) data provide rich temporal supervision, yet existing remote sensing foundation models mainly exploit sequential observations thro

Terrain-Dependent Intra-Cycle Leg Timing for Effective Locomotion on Granular Slopes

arXiv:2610.04144v1 Announce Type: new Abstract: Locomotion on granular slopes such as sand dunes remains a fundamental challenge for legged robots due to reduced shear strength and gravity-induced ani

researcharxiv-cs-ro

The Blind Spot Paradox: When Adaptive Classifiers Defeat Drift Detectors

arXiv:2610.05853v1 Announce Type: new Abstract: Monitoring concept drift from an adaptive classifier's error stream creates an operational conflict with the model's own update loop. When internal adap

TIMBRE: Teaching Time Series Forecasters to Read, Remember, and Reconcile

arXiv:2610.04795v1 Announce Type: new Abstract: Event-informed forecasting requires translating reports and historical responses into changes to a numerical forecast. We propose TIMBRE (Temporal Integ

Transform Trained Transformer for Accelerating Native 4K Video Generation

arXiv:2512.13492v2 Announce Type: replace Abstract: Native 4K (2176imes3840) video generation remains a critical challenge due to the quadratic computational explosion of full-attention as spatiotempo

Two Americas of Well-Being: Divergent Rural-Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

arXiv:2511.10542v2 Announce Type: replace-cross Abstract: Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators o

Underscoring the Problem: Why Softpick Fails at Initialization

arXiv:2610.05488v1 Announce Type: new Abstract: Softmax attention gives every token a nonzero weight, which in trained models concentrates into attention sinks and massive activations that widen the d

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

Tutorials

Variance-Optimal Control Variates for Learning with Black-box Feedback

arXiv:2610.04766v1 Announce Type: new Abstract: Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposi

tutorialsarxiv-cs-lg

Video Replanning via Latent Embedding Refinement and Rejection-Based Sampling

arXiv:2510.17315v3 Announce Type: replace Abstract: Video planning has emerged as a flexible framework for robot manipulation, in which a generative model predicts a video of task completion, and a do

applicationsarxiv-cs-ro

Where Does Jagged Competence Come From?

arXiv:2610.03831v1 Announce Type: new Abstract: Capable systems often show jagged competence: low average error alongside failures on particular inputs. We ask where it comes from in a task built from

ZeST: an VLM-based Zero-Shot Traversability Navigation for Unknown Environments

arXiv:2508.19131v3 Announce Type: replace-cross Abstract: The advancement of robotics and autonomous navigation systems hinges on the ability to accurately predict terrain traversability. Traditional

A Simulation-Grounded Agentic VLM Framework for Wildfire Monitoring and Reporting

arXiv:2610.02451v1 Announce Type: new Abstract: Effective wildfire monitoring requires relating visual evidence to physical fire dynamics, yet real videos with synchronized physical annotations are sc

agentsarxiv-cs-cv

A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News

arXiv:2511.18618v2 Announce Type: replace-cross Abstract: In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effect

A Unified Framework for Empowerment and Predictive Control

arXiv:2610.03563v1 Announce Type: new Abstract: Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost func

safetyarxiv-cs-ro

AgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents

arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def

agentsarxiv-cs-ai

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking

arXiv:2610.02831v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful listwise rerankers for multimodal retrieval, but high inference costs restrict them to evaluating small local

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions

arXiv:2506.05766v2 Announce Type: replace Abstract: Retrieval augmented generation (RAG) has shown great power in improving Large Language Models (LLMs). However, most existing RAG-based LLMs are dedi

applicationsarxiv-cs-cl

Bringing predictive analytics to the agentic AI era

In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled. The big question now is how to enable predictive systems t

agentsmit-tech-review

Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality

arXiv:2603.13725v2 Announce Type: replace Abstract: Memristor-based analog compute-in-memory (CIM) architectures provide a promising substrate for the efficient deployment of Large Language Models (LL

researcharxiv-cs-cl

Capability Scaling-Down Laws for LLM Compression

arXiv:2610.02462v1 Announce Type: cross Abstract: LLM compression reduces inference costs and memory requirements, but selecting a method and configuration remains largely empirical because comparable

researcharxiv-cs-cl

CoMemNet: A Continual Memory Network with Drift-Aware Sampling for Traffic Prediction

arXiv:2605.05738v2 Announce Type: replace-cross Abstract: Traffic sensor networks evolve as sensors are added and traffic distributions change, whereas most forecasting models assume a fixed node set

Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain Shift

arXiv:2610.02364v1 Announce Type: new Abstract: Explainability is increasingly required for perception models in intelligent vehicles, yet whether explanations remain faithful under driving domain shi

Local Ai

Cordial Learning: Distributed Training with Correlated Data

arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent

local-aiarxiv-cs-ai

Deep Bayesian REFoCUS

arXiv:2610.03419v1 Announce Type: new Abstract: In this work we formulate ultrasound multistatic recovery from arbitrary transmit sequences as a Bayesian inference problem. To that end, we train a dee

DEPICT: Scoring Text-to-Image Alignment by Answer Agreement

arXiv:2610.03617v1 Announce Type: new Abstract: Image-text alignment is a core problem in computer vision with applications in caption evaluation, hallucination detection, data curation, and the bench

DeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents

arXiv:2610.02320v1 Announce Type: cross Abstract: Computer-use agents need to reliably ground action targets in complex desktop scenes, where multiple applications, overlapping windows, and visually s

Diffusion-Based Synthetic Data Pretraining for Enhancing Activity Recognition

arXiv:2610.02292v1 Announce Type: cross Abstract: Human activity recognition (HAR) is increasingly important for healthcare, well-being, and daily monitoring ap- plications, for which detecting alimen

applicationsarxiv-cs-ai

Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees

arXiv:2606.16610v2 Announce Type: replace-cross Abstract: Diffusion Flow Matching (DFM) has recently emerged as a versatile framework for generative modeling, yet its theoretical convergence propertie

Distilling Stockfish on a Billion Positions, Full 3.9B Dataset Available [P]

researchr-machinelearning

In this project, I distilled the Stockfish value function into a ResNet/ViT model using 1 billion positions from the Gigafish dataset. The 3.9 billion position dataset is available on huggingface: htt

DriftTTS: Few-Step Text-to-Speech Without Distillation via Distribution-Matching Drift

arXiv:2610.03390v1 Announce Type: cross Abstract: Few-step neural text-to-speech models often rely on short- ened diffusion or flow-matching schedules, or on distillation from pretrained multi-step te

Drive vs. Decay: On the Training Dynamics of Joint-Embedding Predictive Architectures

arXiv:2610.02344v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) are prone to representation collapse, typically mitigated through empirical heuristics. We develop an e

Efficient Neural Field Learning via Adaptive Coverage and Focused Sampling

arXiv:2610.02410v1 Announce Type: cross Abstract: Implicit neural representations (INRs) provide a flexible framework for modeling high-dimensional continuous fields, but their training is often ineff

ENCORE: Exact Non-equilibrium COntrol with Replica Exchange for Diffusion Generation

arXiv:2610.02538v1 Announce Type: cross Abstract: Inference-time control steers a pretrained generative model towards a target distribution without retraining. We study tilted targets pi_0propto G_0,p

Evolving Hybrid Quantum-Classical Architectures for Image Classification

arXiv:2610.03220v1 Announce Type: cross Abstract: Hybrid quantum classical neural networks integrate parameterized quantum circuits (PQCs) with established deep learning architectures, but their perfo

Hardware

Exclusive: Iterate.ai’s Lifeboat runs up to six times more AI agent sessions per GPU

Enterprise artificial intelligence software company Iterate Studio Inc. today launched Lifeboat, an inference engine for large language models that has confidential computing built in. Iterate.ai says

hardwaresiliconangle

EyeRobot 2.0: Active Gaze for Precise Manipulation without Wrist Cameras

arXiv:2610.03710v1 Announce Type: cross Abstract: Inspired by human vision, we introduce a framework using active gaze to enable fine-grained bimanual manipulation with only a single stereo camera. Ey

FSPO: Policy-Consistent Risk and Pareto-Feasible Control for Budgeted LLM RL Post-Training

arXiv:2610.02828v1 Announce Type: new Abstract: Adaptive LLM reinforcement-learning post-training changes multiple training actuators online, including rollout temperature, group size, clipping, KL re

Generalizable single-cell perturbation response prediction using energy-guided flow matching

arXiv:2610.02232v1 Announce Type: cross Abstract: Predicting phenotypic and transcriptional responses to perturbations at single-cell resolution provides a powerful tool for probing biological systems

High-Dimensional Asymptotics and Dataset Selection for Private Transfer Learning

arXiv:2610.02578v1 Announce Type: cross Abstract: To commit to buying external data or participate in collaborative learning, one must decide whether the additional data will improve prediction enough

applicationsarxiv-cs-lg

Hindsight-Guided Rationale Distillation for Rare Disease Diagnosis

arXiv:2610.03176v1 Announce Type: new Abstract: We study hindsight-guided distillation for rare disease diagnosis on ZebraMap: a 1.5B student is fine-tuned on chain-of-thought traces from a 8B teacher

researcharxiv-cs-cl