Search: “models”

A Stability Benchmark of Generative Regularizers for Inverse Problems

arXiv:2605.10076v1 Announce Type: cross Abstract: Generative (diffusion) priors demonstrate remarkable performance in addressing inverse problems in imaging. Yet, for scientific and medical imaging, i

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Hardware

AAAC: Activation-Aware Adaptive Codebooks for 4-bit LLM Weight Quantization

DGX agent

arXiv:2605.08692v1 Announce Type: cross Abstract: Post-training weight-only quantization to 4 bits is widely used to reduce the memory and compute costs of large language model inference. Existing PTQ

hardwarearxiv-cs-cl

12 May 2026

Applications

Absurd World: A Simple Yet Powerful Method to Absurdify the Real-world for Probing LLM Reasoning Capabilities

arXiv:2605.09678v1 Announce Type: new Abstract: While extremely powerful and versatile at various tasks, the thinking capabilities of large language models (LLMs) are often put under scrutiny as they

applicationsarxiv-cs-ai

Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims

arXiv:2605.10575v1 Announce Type: cross Abstract: Safe fine-tuning defenses are often endorsed on the basis of a held-out gap reduction, but the same reduction can come from sampling noise, subject ar

AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation

arXiv:2605.08734v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) reparameterizes a weight update as a product of two low-rank factors, but the Jacobian J_{G} of the generator mapping the f

Applications

Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics

arXiv:2512.13919v2 Announce Type: replace Abstract: This work shows how adaptivity can enhance value realization of digital twins in civil engineering. We focus on adapting the state transition models

applicationsarxiv-cs-lg

Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks

arXiv:2511.06216v4 Announce Type: replace Abstract: Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically r

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

arXiv:2605.08715v1 Announce Type: cross Abstract: LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and

AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks

arXiv:2605.10286v1 Announce Type: new Abstract: Building effective clinical decision support systems requires the synthesis of complex heterogeneous multimodal data. Such modalities include temporal e

Safety

Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation

arXiv:2402.02286v4 Announce Type: replace-cross Abstract: U-shaped architectures have long dominated the field of medical image segmentation, while Transformers are widely employed for modeling long-r

safetyarxiv-cs-ai

AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

arXiv:2509.08031v3 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized too

Safety

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria

arXiv:2605.08354v1 Announce Type: new Abstract: Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human

safetyarxiv-cs-ai

Automated Detection of Abnormalities in Zebrafish Development

arXiv:2605.10464v1 Announce Type: new Abstract: Zebrafish embryos are a valuable model for drug discovery due to their optical transparency and genetic similarity to humans. However, current evaluatio

researcharxiv-cs-cv

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

arXiv:2605.10867v1 Announce Type: cross Abstract: Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and mot

BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition

arXiv:2605.08296v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports broad healthcare and behavior science applications. However, data heterogeneity and the

Beyond Toy Benchmarks: A Systematic Evaluation of OOD Detection Methods For Plant Pathology Classification

arXiv:2605.08618v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is essential for reliable deployment of deep learning systems, yet the majority of existing methods are evaluated on

Black-Box Detection of LLM-Generated Text Using Generalized Jensen-Shannon Divergence

arXiv:2510.07500v2 Announce Type: replace Abstract: We study black-box detection of machine-generated text under practical constraints: the scoring model (proxy LM) may mismatch the unknown source mod

Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction

arXiv:2603.04783v2 Announce Type: replace Abstract: While LLMs demonstrate strong reasoning capabilities when provided with full information in a single turn, they exhibit substantial vulnerability in

Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks

model-releasesarxiv-cs-cl

arXiv:2605.09611v1 Announce Type: new Abstract: This preprint presents an empirical analysis of byte-exact chunk-level deduplication in Retrieval-Augmented Generation (RAG) pipelines. We measure conte

Hardware

CellDX AI Autopilot: Agent-Guided Training and Deployment of Pathology Classifiers

arXiv:2605.10362v1 Announce Type: new Abstract: Training AI models for computational pathology currently requires access to expensive whole-slide-image datasets, GPU infrastructure, deep expertise in

hardwarearxiv-cs-cv

CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis

model-releasesarxiv-cs-cl

arXiv:2510.11233v3 Announce Type: replace Abstract: Depression is a pressing global public health issue, yet publicly available Chinese-language resources for depression risk detection remain scarce a

Combining Mechanical and Agentic Specification Inference for Move

arXiv:2605.10005v1 Announce Type: cross Abstract: In this paper, we describe early work on a specification inference tool for the Move Prover that combines a weakest-precondition (WP) analysis over Mo

Composing diffusion priors with explicit physical context via generative Gibbs sampling

arXiv:2605.10642v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful learned priors, but in scientific sampling the target distribution often depends on physical context that i

Computer Use at the Edge of the Statistical Precipice

arXiv:2605.08261v1 Announce Type: cross Abstract: Evaluating Computer Use Agents (CUAs) on interactive environments is fraught with methodological pitfalls that the field has yet to systematically add

Convergence Analysis of Newton's Method for Neural Networks in the Overparameterized Limit

arXiv:2605.08352v1 Announce Type: new Abstract: A convergence analysis is developed for the regularized Newton method for training neural networks (NNs) in the overparameterized limit. As the number o

Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning

arXiv:2605.08839v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) requires a learning system to learn new classes while retaining previously learned knowledge. However, in real-world sc

CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging

arXiv:2605.08455v1 Announce Type: new Abstract: Debugging CUDA programs has long been challenging because failures often arise from subtle interactions among hardware behavior, compiler decisions, mem

Safety

DGPO: Beyond Pairwise Preferences with Directional Consistent Groupwise Optimization

arXiv:2605.10863v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have made remarkable progress, current preference optimization methods still struggle to align directional consist

safetyarxiv-cs-cl

Discovery of Nonlinear Dynamics with Automated Basis Function Generation

arXiv:2605.09696v1 Announce Type: new Abstract: Discovering governing equations from observational data remains a fundamental challenge in scientific modeling, particularly when the underlying mathema

Discrete Flow Matching: Convergence Guarantees Under Minimal Assumptions

arXiv:2605.08882v1 Announce Type: new Abstract: Flow Matching has recently emerged as a popular class of generative models for simulating a target distribution mu_1 from samples drawn from a source di

Tutorials

Do LLMs Experience an Internal Polylogue? Investigating Reasoning through the Lens of Personas

arXiv:2605.09159v1 Announce Type: new Abstract: Recent work shows that large language models (LLMs) encode behavioural traits ('personas') as linear directions in activation space, often called 'perso

tutorialsarxiv-cs-ai

Do not copy and paste! Rewriting strategies for code retrieval

arXiv:2605.08299v1 Announce Type: cross Abstract: Embedding-based code retrieval often suffers when encoders overfit to surface syntax. Prior work mitigates this by using LLMs to rephrase queries and

Dynamics-Aligned Shared Hypernetworks for Contextual RL under Discontinuous Shifts

arXiv:2602.06550v2 Announce Type: replace-cross Abstract: Zero-shot generalization in contextual reinforcement learning remains a core challenge, particularly when the context is latent and must be in

EconWebArena: Benchmarking Autonomous Agents on Economic Tasks in Realistic Web Environments

model-releasesarxiv-cs-cl

arXiv:2506.08136v3 Announce Type: replace Abstract: We introduce EconWebArena, a benchmark for evaluating autonomous agents on complex, multimodal economic tasks in realistic web environments. The ben

Entropy-informed Decoding: Adaptive Information-Driven Branching

arXiv:2605.09745v1 Announce Type: cross Abstract: Large language models (LLMs) achieve remarkable generative performance, yet their output quality is dependent on the decoding strategy. While sampling

Evaluating Developmental Cognition Capabilities of LLMs

arXiv:2605.08549v1 Announce Type: new Abstract: Conversational AI is increasingly personalized around users' preferences, histories, goals, and knowledge, but much less around how users interpret and

Exactness Matters for Physical Rule Enforcement

arXiv:2605.08285v1 Announce Type: new Abstract: Autoregressive scientific forecasters often enforce physical or structural constraints by repairing each predicted state before feeding it back into the

Featurized Occupation Measures for Structured Global Search in Numerical Optimal Control

model-releasesarxiv-cs-ro

arXiv:2603.16231v2 Announce Type: replace-cross Abstract: Numerical optimal control has long been split between globally structured but dimensionally intractable Hamilton--Jacobi--Bellman (HJB) method

Finer is Better (with the Right Scaling)

arXiv:2605.08565v1 Announce Type: new Abstract: Microscaling is a critical technique for preserving the quality of Large Language Models (LLMs) quantized to ultra-low precision formats. Intuitively, f

Fitting Is Not Enough: Smoothness in Extremely Quantized LLMs

arXiv:2605.08894v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance but incur high deployment costs, motivating extremely low-bit but lossy quantization. Existing

Agents

FocuSFT: Bilevel Optimization for Dilution-Aware Long-Context Fine-Tuning

arXiv:2605.09932v1 Announce Type: new Abstract: Large language models can now process increasingly long inputs, yet their ability to effectively use information spread across long contexts remains lim

agentsarxiv-cs-cl

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

arXiv:2605.08820v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-generated images have become increasingly realistic and readily adaptable to concrete real-world claims, creating new cha

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation

arXiv:2605.08712v1 Announce Type: new Abstract: Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimension

From Mechanistic to Compositional Interpretability

arXiv:2605.08934v1 Announce Type: new Abstract: Mechanistic interpretability aims to explain neural model behaviour by reverse-engineering learned computational structure into human-understandable com

Local Ai

GELATO: Generative Entropy- and Lyapunov-based Adaptive Token Offloading for Device-Edge Speculative LLM Inference

arXiv:2605.10124v1 Announce Type: cross Abstract: The recent growth of on-device Large Language Model (LLM) inference has driven significant interest in device-edge collaborative LLM inference. As a p

local-aiarxiv-cs-lg

Local Ai

Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs

arXiv:2605.10277v1 Announce Type: new Abstract: Operator learning for partial differential equations (PDEs) aims to learn solution operators on infinite-dimensional function spaces from finite-resolut

local-aiarxiv-cs-lg

Global Optimization via Softmin Energy Minimization

arXiv:2509.17815v2 Announce Type: replace Abstract: Global optimization, particularly for non-convex functions with multiple local minima, poses significant challenges for traditional gradient-based m

Hierarchical Reinforced Trader (HRT): A Bi-Level Approach for Optimizing Stock Selection and Execution

arXiv:2410.14927v2 Announce Type: replace-cross Abstract: Automated equity trading requires converting noisy market and news signals into executable portfolio decisions under risk, turnover, and trans