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arXiv:2605.07786v1 Announce Type: cross Abstract: As generative models achieve unprecedented visual quality, the gold standard for image evaluation remains traditional feature-distribution metrics (e.

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Research

Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation

DGX agent

arXiv:2505.22842v4 Announce Type: replace Abstract: Transformer-based language models rely on positional encoding (PE) to handle token order and support context length extrapolation. However, existing

researcharxiv-cs-cl

11 May 2026

Beyond Linear Attention: Softmax Transformers Implement In-Context Reinforcement Learning

arXiv:2605.07333v1 Announce Type: new Abstract: In-context reinforcement learning (ICRL) studies agents that, after pretraining, adapt to new tasks by conditioning on additional context without parame

bispectrum: Selective G-Bispectra Made Practical

arXiv:2605.07270v1 Announce Type: new Abstract: Many machine learning tasks are invariant under the action of a group G of transformations: signal classification can be invariant under translations, i

Breaking QAOA's Fixed Target Hamiltonian Barrier: A Fully Connected Quantum Boltzmann Machine via Bilevel Optimization

arXiv:2605.07473v1 Announce Type: cross Abstract: To overcome the limitations of classical partially connected Boltzmann machines and mainstream quantum Boltzmann machines (QBMs), this work extends th

Bridging the Last Mile of Circuit Design: PostEDA-Bench, a Hierarchical Benchmark for PPA Convergence and DRC Fixing

arXiv:2605.06936v1 Announce Type: cross Abstract: LLM-based agents are increasingly applied to the 'last mile' of Electronic Design Automation (EDA): repairing residual sign-off Design Rule Check (DRC

Applications

Can LLMs Take Retrieved Information with a Grain of Salt?

arXiv:2605.06919v1 Announce Type: new Abstract: Large language models have demonstrated impressive retrieval-augmented capabilities. However, a crucial area remains underexplored: their ability to app

applicationsarxiv-cs-cl

Clinical Characteristics and Laboratory Biomarkers in ICU-admitted Septic Patients with and without Bacteremia

arXiv:2311.08433v3 Announce Type: replace-cross Abstract: Few studies have investigated the diagnostic utilities of biomarkers for predicting bacteremia among septic patients admitted to intensive car

Consistency Regularised Gradient Flows for Inverse Problems

arXiv:2605.07907v1 Announce Type: cross Abstract: Vision-Language Latent Diffusion Models (LDMs) (Rombach et al., 2022) provide powerful generative priors for inverse problems. However, existing LDM-b

researcharxiv-cs-cv

Convergence and Emergence of In-Context Reinforcement Learning with Chain of Thought

arXiv:2605.07123v1 Announce Type: new Abstract: In-context reinforcement learning (ICRL) refers to the ability of RL agents to adapt to new tasks at inference time without parameter updates by conditi

Convex Optimization with Nested Evolving Feasible Sets

arXiv:2605.07386v1 Announce Type: new Abstract: Convex Optimization with Nested Evolving Feasible Sets (CONES)} is considered where the objective function f remains fixed but the feasible region evolv

Curvature Beyond Positivity: Greedy Guarantees for Arbitrary Submodular Functions

arXiv:2605.07902v1 Announce Type: new Abstract: Submodular functions -- functions exhibiting diminishing returns -- are central to machine learning. When the objective is monotone and non-negative, th

Safety

Decoupling Semantics and Fingerprints: A Universal Representation for AI-Generated Image Detection

arXiv:2605.07074v1 Announce Type: new Abstract: Detecting AI-generated images across unseen architectures remains challenging, as existing models often overfit to generator-specific fingerprints and s

safetyarxiv-cs-cv

Demystifying Lipschitz verification: positive matrices, negative results

arXiv:2603.28113v2 Announce Type: replace Abstract: The global Lipschitz constant of a neural network is related to robustness and generalization, yet unlike in many classical models, it is not plainl

Applications

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks

arXiv:2506.13351v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) training of large language models (LLMs) on unverifiable tasks is challenging even when a reasonable-quality refer

applicationsarxiv-cs-ai

Safety

Direction-Flipped Influence Audits Reveal Hidden Structure in Moral Choices of LLMs

arXiv:2602.22831v2 Announce Type: replace-cross Abstract: Moral benchmarks for LLMs typically score models on context-free prompts, implicitly treating the measured choice rate as stable. We test this

safetyarxiv-cs-ai

DKDS: A Benchmark Dataset of Degraded Kuzushiji Documents with Seals for Detection and Binarization

model-releasesarxiv-cs-cv

arXiv:2511.09117v4 Announce Type: replace Abstract: Kuzushiji, a pre-modern Japanese cursive script, can currently be read and understood by only a few thousand trained experts in Japan. With the rapi

Applications

Ensemble Learning for Healthcare: A Comparative Analysis of Hybrid Voting and Ensemble Stacking in Obesity Risk Prediction

arXiv:2509.02826v2 Announce Type: replace-cross Abstract: Obesity is a critical global health issue driven by dietary, physiological, and environmental factors, and is strongly associated with chronic

applicationsarxiv-cs-ai

Estimation of Motor Unit Parameters from Surface Electromyograms using an Informed Autoencoder

arXiv:2605.07458v1 Announce Type: new Abstract: Motor unit parameters such as the innervation zone centre or the conduction velocity of the electrical potential harbour the potential to improve the fi

Local Ai

Eulerian Motion Guidance: Robust Image Animation via Bidirectional Geometric Consistency

arXiv:2605.06280v2 Announce Type: replace Abstract: Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks

local-aiarxiv-cs-cv

Evaluating Prompt Injection Defenses for Educational LLM Tutors: Security-Usability-Latency Trade-offs

arXiv:2605.06669v1 Announce Type: cross Abstract: Educational LLM tutors face a core AI alignment challenge: they must follow user intent while preserving pedagogical constraints and safety policies.

Exact Regular-Constrained Variable-Order Markov Generation via Sparse Context-State Belief Propagation

arXiv:2605.07839v1 Announce Type: new Abstract: Variable-order Markov models generate sequences over a finite alphabet by conditioning each symbol on the longest available suffix of the generated hist

EyeCue: Driver Cognitive Distraction Detection via Gaze-Empowered Egocentric Video Understanding

arXiv:2605.07859v1 Announce Type: new Abstract: Driver cognitive distraction is a major cause of road collisions and remains difficult to detect. Unlike manual or visual distraction, cognitive distrac

researcharxiv-cs-cv

Factored Classifier-Free Guidance

arXiv:2506.14399v5 Announce Type: replace-cross Abstract: Counterfactual generation aims to simulate realistic hypothetical outcomes under causal interventions. Diffusion models have emerged as a powe

FANoS-v2: Feedback-Controlled Momentum with Thermostat Damping for Lightweight Neural Optimization

arXiv:2601.00889v2 Announce Type: replace Abstract: FANOS{} is a PyTorch optimizer that augments RMS-preconditioned momentum with a scalar feedback controller over update energy. The public reference

FlashMol: High-Quality Molecule Generation in as Few as Four Steps

arXiv:2605.07020v1 Announce Type: cross Abstract: Generating chemically valid 3D molecular conformations is critical for computational drug discovery. Classical diffusion-based models like GeoLDM perf

Flat Channels to Infinity in Neural Loss Landscapes

arXiv:2506.14951v4 Announce Type: replace-cross Abstract: The loss landscapes of neural networks contain minima and saddle points that may be connected in flat regions or appear in isolation. We ident

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems

arXiv:2506.04565v2 Announce Type: replace-cross Abstract: Compound AI Systems (CAIS) are an emerging paradigm that integrates large language models (LLMs) with external components, including retriever

researcharxiv-cs-cl

GC-ART: Global Learnable Second-Order Rational Tone Curves for Illumination Robustness

model-releasesarxiv-cs-cv

arXiv:2605.07329v1 Announce Type: new Abstract: We introduce GC-ART (Global Curve Adaptive Rational Tone-mapping), a lightweight differentiable pre-processing module for robust image classification. G

Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS

arXiv:2502.17500v3 Announce Type: replace-cross Abstract: This paper investigates in depth the fundamental properties of the two-parameter generalized Euler logarithm and its inverse, the associated d

Gradient-Based LoRA Rank Allocation Under GRPO: An Empirical Study

model-releasesarxiv-cs-cl

arXiv:2605.07366v1 Announce Type: new Abstract: Adaptive rank allocation for LoRA, allocating more parameters to important layers and fewer to unimportant ones, consistently improves efficiency under

Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works

arXiv:2605.07689v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is a standard algorithm for reinforcement learning from verifiable rewards, but its group-mean-centered advant

Hammer and Anvil: Toward a Theory of Backdoors in Federated Learning

arXiv:2509.08089v2 Announce Type: replace Abstract: Federated Learning (FL) enables distributed model training but is vulnerable to backdoor attacks, where malicious clients embed attacker-controlled

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents

arXiv:2605.07177v1 Announce Type: cross Abstract: Existing multimodal search agents process target entities sequentially, issuing one tool call per entity and accumulating redundant interaction rounds

In-Context Credit Assignment via the Core

arXiv:2605.06920v1 Announce Type: cross Abstract: We propose incentive-aligned mechanisms for in-context credit assignment: the task of assigning credit for AI-generated content (e.g. code, news artic

Interpreting Speaker Characteristics in the Dimensions of Self-Supervised Speech Features

arXiv:2603.03096v2 Announce Type: replace-cross Abstract: How do speech models trained through self-supervised learning structure their representations? Previous studies have looked at how information

researcharxiv-cs-cl

Learning Agent Routing From Early Experience

model-releasesarxiv-cs-cl

arXiv:2605.07180v1 Announce Type: new Abstract: LLM agents achieve strong performance on complex reasoning tasks but incur high latency and compute cost. In practice, many queries fall within the capa

Learning Material-Aware Hamiltonian Risk Fields for Safe Navigation

arXiv:2605.07038v1 Announce Type: new Abstract: Risk-aware navigation should be selective: a policy should expose evasive degrees of freedom only when the local scene admits a lower-risk feasible mane

LENS: Low-Frequency Eigen Noise Shaping for Efficient Diffusion Sampling

arXiv:2605.07253v1 Announce Type: new Abstract: Distilled diffusion models accelerate image generation by reducing the number of denoising steps, but often suffer from degraded image quality. To mitig

researcharxiv-cs-cv

LensVLM: Selective Context Expansion for Compressed Visual Representation of Text

arXiv:2605.07019v1 Announce Type: cross Abstract: Vision Language Models (VLMs) offer the exciting possibility of processing text as rendered images, bypassing the need for tokenizing the text into lo

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

arXiv:2508.16571v4 Announce Type: replace Abstract: In this paper, we describe and benchmark a competitor-discovery component used within an agentic AI system for fast drug asset due diligence. A comp

Agents

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling

arXiv:2605.08083v1 Announce Type: new Abstract: Test-time scaling (TTS) has become an effective approach for improving large language model performance by allocating additional computation during infe

agentsarxiv-cs-cl

Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate

arXiv:2605.07342v1 Announce Type: cross Abstract: Compile-pass rate is the dominant evaluation signal for LLM code generation, yet for multi-component domain-specific artifacts it can be actively misl

Mean-Pooled Cosine Similarity is Not Length-Invariant: Theory and Cross-Domain Evidence for a Length-Invariant Alternative

model-releasesarxiv-cs-cl

arXiv:2605.07345v1 Announce Type: new Abstract: Mean-pooled cosine similarity is the default metric for comparing neural representations across languages, modalities, and tasks. We establish that this

Minerva: Reinforcement Learning with Verifiable Rewards for Cyber Threat Intelligence LLMs

arXiv:2602.00513v3 Announce Type: replace Abstract: Cyber threat intelligence (CTI) analysts routinely convert noisy, unstructured security artifacts into standardized, automation-ready representation

MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference

arXiv:2605.07363v1 Announce Type: cross Abstract: DeepSeek Sparse Attention (DSA) sets the state of the art for fine-grained inference-time sparse attention by introducing a learned token-wise indexer

Local Ai

Modulated learning for private and distributed regression with just a single sample per client device

arXiv:2605.07233v1 Announce Type: new Abstract: This work focuses on the question of learning from a large number of devices with each device holding only a single sample of data. Several real-world a

local-aiarxiv-cs-lg

Motion-o: Trajectory-Grounded Video Reasoning

arXiv:2603.18856v2 Announce Type: replace-cross Abstract: Recent video reasoning models increasingly produce spatio-temporal evidence chains that localize objects at specific timestamps. While these t