Search: “models”

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference

arXiv:2511.21513v2 Announce Type: replace Abstract: Deploying Transformer models on edge devices is limited by latency and energy budgets. While INT8 quantization effectively accelerates the primary m

researcharxiv-cs-lg

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IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment

DGX agent

arXiv:2603.19862v2 Announce Type: replace Abstract: Vision-Language Models like CLIP are extensively used for inter-modal tasks which involve both visual and text modalities. However, when the individ

safetyarxiv-cs-cv

1 Jun 2026

KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems

arXiv:2605.31596v1 Announce Type: new Abstract: Diffusion models have shown promising performance as data-driven priors for computational imaging, as well as some capacity to detect out-of-distributio

researcharxiv-cs-cv

Learning-Based Navigation for Indoor Mobile Robots

model-releasesarxiv-cs-ro

arXiv:2605.30468v1 Announce Type: new Abstract: This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, tra

Learning Multi-Agent Coordination via Sheaf-ADMM

arXiv:2605.31005v1 Announce Type: new Abstract: We present a differentiable optimization framework for multi-agent coordination. An input is decomposed into overlapping local views, each processed by

Tutorials

Learning Permutation-invariant Macroscopic Dynamics

arXiv:2605.30812v1 Announce Type: new Abstract: Accurately modeling the macroscopic dynamics of high-dimensional microscopic systems is of broad interest across the sciences. Many data-driven approach

tutorialsarxiv-cs-lg

Learning Randomized Reductions

arXiv:2412.18134v4 Announce Type: replace Abstract: Randomized self-reductions (RSRs) express f(x) using f evaluated at random correlated points, enabling self-correcting programs, instance-hiding pro

Linear Ordering Problem: Time for a Change

arXiv:2605.31051v1 Announce Type: cross Abstract: The Linear Ordering Problem (LOP) is a fundamental combinatorial optimization problem with important applications in areas such as economics, social c

Agents

LLM Anonymization Against Agentic Re-Identificatio

arXiv:2605.30848v1 Announce Type: cross Abstract: Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-ident

agentsarxiv-cs-cl

Local linear convergence of gradient methods for overparameterized Gaussian mixtures

arXiv:2605.30936v1 Announce Type: new Abstract: We study the problem of learning Gaussian mixture models under overparameterization. Prior work has shown that while overparameterization is essential f

local-aiarxiv-cs-lg

Agents

LongTraceRL: Learning Long-Context Reasoning from Search Agent Trajectories with Rubric Rewards

arXiv:2605.31584v1 Announce Type: cross Abstract: Long-context reasoning remains a central challenge for large language models, which often fail to locate and integrate key information in extensive di

agentsarxiv-cs-ai

MAAT: Multi-phase Adapter-Aware Targeted Unlearning

model-releasesarxiv-cs-cl

arXiv:2605.30514v1 Announce Type: cross Abstract: Machine unlearning evaluation is structurally skewed: Why-type questions, which probe causal and relational knowledge, comprise less than 0.06% of Cou

Applications

MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding

arXiv:2605.30794v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question answering (VQA) tasks. However, they re

applicationsarxiv-cs-ai

Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning

arXiv:2602.13069v2 Announce Type: replace-cross Abstract: On-device fine-tuning enables privacy-preserving personalization of large language models, but mobile devices impose severe memory constraints

local-aiarxiv-cs-cl

Mixture of Concept Bottleneck Experts

arXiv:2602.02886v2 Announce Type: replace-cross Abstract: Concept Bottleneck Models (CBMs) promote interpretability by grounding predictions in human-understandable concepts. However, existing CBMs ty

Mixture of Horizons in Action Chunking

arXiv:2511.19433v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have shown remarkable capabilities in robotic manipulation, but their performance is sensitive to the extb

local-aiarxiv-cs-ai

Neuro-symbolic Syntactic Parsing: Shaping a Neural Network with the CYK Algorithm

arXiv:2605.31421v1 Announce Type: cross Abstract: In this paper, we show the possibility of a direct injection of algorithms into neural network architecture. We focus on a complex algorithm, that is,

nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2605.31572v1 Announce Type: new Abstract: Reasoning is essential for autonomous driving (AD) in long-tail scenarios, where vehicles must apply commonsense knowledge, understand spatial relations

On the impact of retrieved content representations in RAG Pipelines

arXiv:2605.30790v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) supplements a language model's input with retrieved documents, yet most RAG pipelines inherit retrieval component

On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders

arXiv:2605.31518v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose neural network activations into interpretable features, but many learned features never activate, a problem called

safetyarxiv-cs-lg

Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory

arXiv:2602.06902v2 Announce Type: replace Abstract: In this paper, we study dynamic regret in unconstrained online convex optimization (OCO) with movement costs. Specifically, we generalize the standa

Physics Enhanced Deep Surrogates for the Phonon Boltzmann Transport Equation

arXiv:2512.05976v3 Announce Type: replace-cross Abstract: Designing materials with controlled heat flow at the nano-scale is central to advances in microelectronics, thermoelectrics, and energy-conver

Applications

Positional versus Symbolic Attention Heads: Learning Dynamics, RoPE Geometry, and Length Generalization

arXiv:2605.31558v1 Announce Type: cross Abstract: Transformer-based language models are widespread in today's society. As such, understanding the mechanisms by which they solve structured tasks and pr

applicationsarxiv-cs-ai

Probing the Prompt KV Cache: Where It Becomes Dispensable

model-releasesarxiv-cs-cl

arXiv:2605.30574v1 Announce Type: new Abstract: Prior KV cache compression schemes empirically demonstrate that the prompt cache is partially redundant during decoding, dropping or summarising entries

Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes

arXiv:2601.20076v2 Announce Type: replace-cross Abstract: We consider minimizing an objective function subject to constraints defined by the intersection of lower-level sets of convex functions. We st

Rationalize: Shared Semantic Reasoning for Human-AI Alignment

arXiv:2605.30632v1 Announce Type: cross Abstract: We introduce Rationalize, a role-pair framework for shared semantic reasoning between humans and AI models in data-driven sensemaking. Building on ide

Tutorials

Reliable Self-Improvement Training by Verifying Reasoning, Not Just Answers

arXiv:2603.21558v2 Announce Type: replace Abstract: Self-improvement training, where models learn from self-generated solutions, promises sustained capability gains but suffers from a pervasive failur

tutorialsarxiv-cs-ai

Scalable Inference-Time Annealing with Surrogate Likelihood Estimators

arXiv:2605.31498v1 Announce Type: new Abstract: A long standing challenge in computational chemistry and biophysics is efficiently sampling the Boltzmann distribution of molecules. Advances in generat

researcharxiv-cs-lg

Self-Reflective Generation at Test Time

arXiv:2510.02919v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly solve complex reasoning tasks via long chain-of-thought, but their forward-only autoregressive generation

researcharxiv-cs-cl

Self-Tuning Regularization for Image Scanning Microscopy

model-releasesarxiv-cs-cv

arXiv:2605.31426v1 Announce Type: cross Abstract: Image Scanning Microscopy (ISM) is a fluorescence imaging technique that combines detector-array acquisition and computational reconstruction to achie

Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense

arXiv:2605.30837v1 Announce Type: cross Abstract: Prompt-injection detectors are heterogeneous: each is strong on a different slice of attacks, and none is always reliable. Yet existing systems still

SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs

arXiv:2603.20253v2 Announce Type: replace-cross Abstract: Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental reso

SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning

arXiv:2605.30832v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models have significantly improved chain-of-thought (CoT) capabilities via reinforcement learning (RL). However, gene

Social welfare optimisation under institutional reward and punishment

arXiv:2605.31330v1 Announce Type: cross Abstract: Institutional incentives are widely used to promote cooperation among autonomous, self-regarding agents, from human societies to multi-agent and AI sy

Softsign: Smooth Sign in Your Optimizer For Better Parameter Heterogeneity Handling

arXiv:2605.31371v1 Announce Type: new Abstract: Sign-based and LMO-inspired optimizers have recently attracted substantial attention in deep learning due to their strong performance and low memory foo

Stateful Online Monitoring Catches Distributed Agent Attacks

arXiv:2605.31593v1 Announce Type: cross Abstract: Language models can find thousands of severe software vulnerabilities, and agents are increasingly being misused for cyberattacks. To avoid detection,

The Geometry of Activity Cliffs: Representation Dependence and Multi-Scale Characterization of Activity Landscapes

arXiv:2605.30831v1 Announce Type: cross Abstract: Activity cliffs, structurally similar compounds with large potency differences, are widely treated as intrinsic features of chemical datasets. We argu

The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI

arXiv:2603.00068v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined eve

Towards Efficient LLMs Annealing with Principled Sample Selection

arXiv:2605.31175v1 Announce Type: new Abstract: The annealing phase is a pivotal convergence stage in LLM pre-training that ultimately determines final model quality. However, effectively selecting tr

researcharxiv-cs-cl

Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits

arXiv:2605.30913v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in conversational settings where user tone ranges from polite to adversarial or toxic, yet less

TUX: Measuring Human--AI Tacit Understanding

arXiv:2605.30930v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly act as collaborative partners, human--AI alignment is often evaluated through explicit task success, accu

Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization

arXiv:2506.22304v3 Announce Type: replace-cross Abstract: Continuous Normalizing Flows (CNFs) enable elegant generative modeling but remain bottlenecked by their iterative nature requiring costly samp

safetyarxiv-cs-cv

Variational Adapter for Cross-modal Similarity Representation

arXiv:2605.30968v1 Announce Type: cross Abstract: The core of vision-language models lies in measuring cross-modal similarity within a unified representation space. However, most image-text matching o

Applications

VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning

arXiv:2605.31457v1 Announce Type: new Abstract: With the rapid advancement of large multimodal models (LMMs), inference-time overhead has become a key bottleneck for real-world deployment. Existing me

applicationsarxiv-cs-cv

What changes after deployment? A survey on On-device Learning in TinyML

arXiv:2605.31226v1 Announce Type: cross Abstract: Machine learning models on microcontroller-class devices (TinyML) face a fundamental challenge: post-deployment distribution change undermines static

local-aiarxiv-cs-ai

A Computational Method for Solving the Stochastic Joint Replenishment Problem in High Dimensions

arXiv:2511.11830v2 Announce Type: replace-cross Abstract: We consider a discrete-time formulation for a class of high-dimensional stochastic joint replenishment problems. First, we approximate the pro

29 May 2026

A new completely parameter-free clustering algorithm for unsupervised classification of BATSE gamma-ray bursts

arXiv:2605.30175v1 Announce Type: cross Abstract: Cluster analysis is a widely applied machine learning technique to understand the existing patterns in the population of gamma-ray bursts (GRBs), in o

29 May 2026

A Progress-Aware Leader-Follower Midair Docking System for Dual-Drone Aerial Manipulation