Isolater - Feed

Ax Vaibhav Singh, Oleksiy Ostapenko, Pierre-Andr\'e No\"el, Eugene Belilovsky, Torsten Scholak 3/2/2026

DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone

DiffuMamba: diffusion language model with Mamba backbone for efficient masked sequence modeling, achieving linear-time complexity vs Transformer quadratic overhead.

Ax Siqiao Mu, Diego Klabjan 3/2/2026

Descend or Rewind? Stochastic Gradient Descent Unlearning

Analysis of stochastic gradient descent-based unlearning algorithms (D2D and R2D) with provable guarantees for removing training data impact.

Ax Tao Zhe, Huazhen Fang, Kunpeng Liu, Qian Lou, Tamzidul Hoque, Dongjie Wang 3/2/2026

Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation

Multi-agent reinforcement learning approach using attention for automated feature transformation in structured data processing.

Ax Timoth\'ee Chauvin, Erwan Le Merrer, Fran\c{c}ois Ta\"iani, Gilles Tredan 3/2/2026

Log Probability Tracking of LLM APIs

Method for monitoring LLM API consistency over time by tracking log probability changes to detect undisclosed model updates.

Ax Bart{\l}omiej Starosta, S{\l}awomir T. Wierzcho\'n, Piotr Borkowski, Dariusz Czerski, Marcin Sydow, Eryk Laskowski, Mieczys{\l}aw A. K{\l}opotek 3/2/2026

Rough Sets for Explainability of Spectral Graph Clustering

Rough sets method for explaining results of spectral graph clustering algorithms applied to document data.

Ax Ali Al Sahili, Ali Chehab, Razane Tajeddine 3/2/2026

On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models

Study on membership inference attacks for extracting training data from LLMs, demonstrating privacy risks through coordinated extraction and verification techniques.

Ax Aaron Defazio, Konstantin Mishchenko, Parameswaran Raman, Hao-Jun Michael Shi, Lin Xiao 3/2/2026

Smoothing DiLoCo with Primal Averaging for Faster Training of LLMs

Generalized Primal Averaging (GPA) optimizer for faster LLM training, extending Nesterov's method and unifying recent averaging-based approaches like DiLoCo.

Ax Yingru Li, Jiacai Liu, Jiawei Xu, Yuxuan Tong, Ziniu Li, Qian Liu, Baoxiang Wang 3/2/2026

Trust Region Masking for Long-Horizon LLM Reinforcement Learning

Trust region masking technique for LLM reinforcement learning to address off-policy divergence in policy gradient training of large language models.

Ax Boyang Wang, Yash Vishe, Xin Xu, Zachary Novack, Xunyi Jiang, Julian McAuley, Junda Wu 3/2/2026

CSyMR: Benchmarking Compositional Music Information Retrieval in Symbolic Music Reasoning

CSyMR benchmark for evaluating LLMs on compositional music information retrieval tasks requiring multi-step reasoning over symbolic music notation.

Ax Yisheng Zhong, Zhengbang Yang, Zhuangdi Zhu 3/2/2026

DUET: Distilled LLM Unlearning from an Efficiently Contextualized Teacher

DUET method for LLM unlearning using distilled teacher models to remove undesirable knowledge efficiently while avoiding catastrophic forgetting.

Ax Filippo Portera 3/2/2026

Convex Loss Functions for Support Vector Machines (SVMs) and Neural Networks

Novel convex loss functions for SVMs in binary classification and regression with mathematical derivations and small-scale experiments.

Ax Quang-Huy Nguyen, Zongliang Yue, Hao Chen, Wei-Shinn Ku, Jiaqi Wang 3/2/2026

Federated-inspired Single-cell Batch Integration in Latent Space

Federated-inspired batch correction for single-cell RNA sequencing without centralizing high-dimensional datasets.

Ax Mingyue Cheng, Xiaoyu Tao, Qi Liu, Ze Guo, Enhong Chen 3/2/2026

Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

Position paper proposing agentic framework for time series forecasting with iterative refinement and adaptation.

Ax Haocheng Xi, Shuo Yang, Yilong Zhao, Muyang Li, Han Cai, Xingyang Li, Yujun Lin, Zhuoyang Zhang, Jintao Zhang, Xiuyu Li, Zhiying Xu, Jun Wu, Chenfeng Xu, Ion Stoica, Song Han, Kurt Keutzer 3/2/2026

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

KV-cache quantization to 2-bit precision enabling long video generation on resource-constrained hardware.

Ax Jaewon Lee, Yongwoo Kim, Donghyun Kim 3/2/2026

Erase at the Core: Representation Unlearning for Machine Unlearning

Machine unlearning method addressing superficial forgetting by targeting core feature representations rather than logits.

Ax Sajad Ashkezari 3/2/2026

Robust Online Learning

Online learning framework for training robust classifiers under adversarially chosen clean data and labels.

Ax Ziyang Yu, Wenbing Huang, Yang Liu 3/2/2026

Unified Biomolecular Trajectory Generation via Pretrained Variational Bridge

Pretrained variational bridge for efficient molecular dynamics trajectory generation across diverse molecular systems.

Ax Iv\'an Arcuschin, David Chanin, Adri\`a Garriga-Alonso, Oana-Maria Camburu 3/2/2026

Biases in the Blind Spot: Detecting What LLMs Fail to Mention

Automated detection pipeline for unverbalized biases in LLM chain-of-thought reasoning without predefined categories.

Ax Zhen Bi, Xueshu Chen, Luoyang Sun, Yuhang Yao, Qing Shen, Jungang Lou, Cheng Deng 3/2/2026

RooflineBench: A Benchmarking Framework for On-Device LLMs via Roofline Analysis

Performance characterization framework for small language models on edge devices using Roofline model analysis.

Ax Zhongzheng Qiao, Sheng Pan, Anni Wang, Viktoriya Zhukova, Yong Liu, Xudong Jiang, Qingsong Wen, Mingsheng Long, Ming Jin, Chenghao Liu 3/2/2026

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

Benchmarking framework for time series foundation models addressing data quality, task alignment, and evaluation rigor.

Ax Neelay Velingker, Alaia Solko-Breslin, Mayank Keoliya, Seewon Choi, Jiayi Xin, Anika Marathe, Alireza Oraii, Rajat Deo, Sameed Khatana, Rajeev Alur, Mayur Naik, Eric Wong 3/2/2026

CAMEL: An ECG Language Model for Forecasting Cardiac Events

ECG language model for cardiac event forecasting and report generation from electrocardiogram recordings.

Ax Daniel Romero-Alvarado, Fernando Mart\'inez-Plumed, Lorenzo Pacchiardi, Hugo Save, Siddhesh Milind Pawar, Behzad Mehrbakhsh, Pablo Antonio Moreno Casares, Ben Slater, Paolo Bova, Peter Romero, Zachary R. Tyler, Jonathan Prunty, Luning Sun, Jose Hernandez-Orallo 3/2/2026

Capabilities Ain't All You Need: Measuring Propensities in AI

Framework for measuring propensities (behavioral tendencies) in AI models beyond capability assessment using Item Response Theory.

Ax Sacchit Kale, Piyushi Manupriya, Pierre Marion, Francis Bach, Anant Raj 3/2/2026

Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression

Theoretical analysis of gradient descent convergence rates under large step sizes in separable logistic regression.

Ax Yijiashun Qi, Hanzhe Guo, Yijiazhen Qi 3/2/2026

Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks

Heterogeneous graph neural network model predicting high-potential small/medium enterprises using public data.

Ax Karthik Elamvazhuthi, Abhijith Jayakumar, Andrey Y. Lokhov 3/2/2026

Discrete Diffusion with Sample-Efficient Estimators for Conditionals

Discrete diffusion framework using sample-efficient conditional probability estimators for discrete state space generation.

Ax Junchen Liu, Sven Elflein, Or Litany, Zan Gojcic, Ruilong Li 3/2/2026

Test-Time Training with KV Binding Is Secretly Linear Attention

Analysis showing test-time training with KV binding functions as learned linear attention rather than memorization.

Ax Alina Devkota, Jacob Thrasher, Donald Adjeroh, Binod Bhattarai, Prashnna K. Gyawali 3/2/2026

FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning

Federated learning aggregation method (FedVG) using gradient guidance to address client drift and data heterogeneity.

Ax Darshan Gadginmath, Ahmed Allibhoy, Fabio Pasqualetti 3/2/2026

Provably Safe Generative Sampling with Constricting Barrier Functions

Safety filtering framework for flow-based generative models with formal guarantees on constraint satisfaction.

Ax Chengrui Qu, Yizhou Zhang, Nicolas Lanzetti, Eric Mazumdar 3/2/2026

Training Generalizable Collaborative Agents via Strategic Risk Aversion

Strategic risk aversion approach for training collaborative AI agents that generalize better with new partners.

Ax Yicheng Bao, Xuhong Wang, Qiaosheng Zhang, Chaochao Lu, Xia Hu, Xin Tan 3/2/2026

To Deceive is to Teach? Forging Perceptual Robustness via Adversarial Reinforcement Learning

Adversarial reinforcement learning dataset (AOT-SFT) to improve robustness of multimodal LLMs on visually complex scenes.

Ax Sarthak Munshi, Manish Bhatt, Vineeth Sai Narajala, Idan Habler, Ammar Al-Kahfah, Ken Huang, Blake Gatto 3/2/2026

Manifold of Failure: Behavioral Attraction Basins in Language Models

Maps failure regions in LLMs using MAP-Elites quality diversity search to characterize unsafe behaviors and vulnerabilities.

Ax Timothy Oladunni, Blessing Ojeme, Kyndal Maclin, Clyde Baidoo 3/2/2026

When Should a Model Change Its Mind? An Energy-Based Theory and Regularizer for Concept Drift in Electrocardiogram (ECG) Signals

Energy-based theory for detecting concept drift in ECG signals, distinguishing physiologically plausible variation from true distribution shift.

Ax Junghyun Lee, Minju Hong, Kwang-Sung Jun, Chulhee Yun, Se-Young Yun 3/2/2026

Regularized Online RLHF with Generalized Bilinear Preferences

Regularized online RLHF for Nash Equilibrium identification with generalized bilinear preferences modeling intransitive preferences.

Ax Tianjun Yao, Yongqiang Chen, Yujia Zheng, Pan Li, Zhiqiang Shen, Kun Zhang 3/2/2026

ParamMem: Augmenting Language Agents with Parametric Reflective Memory

ParamMem augments language agents with parametric reflective memory to improve reasoning through diverse self-reflection.

Ax Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy 3/2/2026

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case

Theoretical framework for stationary kernels and Gaussian processes on Lie groups and homogeneous spaces in compact case.

Ax Daniele Zambon, Cesare Alippi 3/2/2026

Assessment of Spatio-Temporal Predictors in the Presence of Missing and Heterogeneous Data

Assesses quality of deep learning models for spatio-temporal prediction with missing and heterogeneous data.

Ax Xiucai Ding, Rong Ma 3/2/2026

Kernel spectral joint embeddings for high-dimensional noisy datasets using duo-landmark integral operators

Kernel spectral joint embeddings using duo-landmark integral operators for integrative analysis of noisy high-dimensional datasets.

Ax Jared Deighton, Wyatt Mackey, Ioannis Schizas, David L. Boothe Jr., Vasileios Maroulas 3/2/2026

Spectral-Stimulus Information for Self-Supervised Stimulus Encoding

Studies spectral-stimulus information for self-supervised encoding of spatial navigation in neurons, exploring place cell population coding.

Ax Takashi Furuya, Anastasis Kratsios 3/2/2026

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs

Analyzes polynomial scaling complexity for neural operator approximations of structured families of backward stochastic differential equations.

Ax Ankur Sinha, Chaitanya Agarwal, Pekka Malo 3/2/2026

FinBloom: Knowledge Grounding Large Language Model with Real-time Financial Data

FinBloom presents a knowledge-grounding approach for LLMs to handle real-time financial queries with live data integration.

Ax Anton Selitskiy, Maitreya Kocharekar 3/2/2026

Discrete Optimal Transport and Voice Conversion

Uses discrete optimal transport with barycentric projection for voice conversion by aligning speaker embeddings.

Ax Tim Schneider, Cristiana de Farias, Roberto Calandra, Liming Chen, Jan Peters 3/2/2026

Apple: Toward General Active Perception via Reinforcement Learning

Apple proposes general active perception via reinforcement learning to handle uncertainty in partially observable robotic environments.

Ax Jing Nathan Yan, Emma Harvey, Junxiong Wang, Jeffrey M. Rzeszotarski, Allison Koenecke 3/2/2026

Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems

Interview study of ML practitioners at Big Tech examining how fairness is approached in real-world recommender systems deployment.

Ax Hexuan Deng, Wenxiang Jiao, Xuebo Liu, Jun Rao, Min Zhang 3/2/2026

REA-RL: Reflection-Aware Online Reinforcement Learning for Efficient Reasoning

REA-RL uses online reinforcement learning with reflection to reduce overthinking and inference costs in large reasoning models.

Ax Yingrui Zhuang, Lin Cheng, Yuji Cao, Tongxin Li, Ning Qi, Yan Xu, Yue Chen 3/2/2026

Quantum Learning and Estimation for Coordinated Operation between Distribution Networks and Energy Communities

Applies quantum learning methods to coordinate energy distribution networks and communities using price signals.

Ax Sijie Li, Weiwei Sun, Shanda Li, Ameet Talwalkar, Yiming Yang 3/2/2026

CoMind: Towards Community-Driven Agents for Machine Learning Engineering

CoMind introduces MLE-Live, a framework for evaluating LLM agents that engage with research communities in ML engineering tasks.

Ax Nathan Mitchell, Lander Ver Hoef, Imme Ebert-Uphoff, Kristina Moen, Kyle Hilburn, Yoonjin Lee, Emily J. King 3/2/2026

Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery

Uses Explainable Boosting Machines to identify overshooting tops in satellite imagery for weather forecasting, emphasizing interpretability in high-stakes ML.

Ax Sajjad Ghiasvand, Mahnoosh Alizadeh, Ramtin Pedarsani 3/2/2026