All entries

AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code

arXiv:2605.17978v1 Announce Type: new Abstract: Vectorization via Single Instruction, Multiple Data (SIMD) architectures is a cornerstone of high-performance computing. To fully exploit hardware poten

researcharxiv-cs-cl

Avoiding Structural Failure Modes in Tabular Fair SSL: Online Primal-Dual Allocation under Confidence Gating

DGX agent

arXiv:2605.16446v1 Announce Type: cross Abstract: Semi-supervised learning (SSL) enables prediction with limited labels, but high-stakes tabular applications (medical, credit, recidivism) require stat

safetyarxiv-cs-ai

19 May 2026

Agents

Awesome deep dive into how we built Engine from @palashshah

This post likely documents the technical architecture and development process behind Engine, a software component or platform, shared by Palash Shah. The content presumably covers key design decisions

agentsharrison-chase--x

Local Ai

Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation

arXiv:2605.16768v1 Announce Type: new Abstract: Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle wi

local-aiarxiv-cs-cv

Local Ai

b9222

local-aillama-cpp-releases

B9222 is a llama.cpp release that adds support for the TRI (Triangle) operation in the Hexagon HTP backend with HVX kernel additions . The release includes optimizations for Hexagon hardware accelerat

Agents

Baba in Wonderland: Online Self-Supervised Dynamics Discovery for Executable World Models

arXiv:2605.16725v1 Announce Type: new Abstract: Executable world models can be read, edited, executed, and reused for planning, but only if the program captures the environment's transition law rather

agentsarxiv-cs-ai

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling

arXiv:2605.17971v1 Announce Type: cross Abstract: Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuri

BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting

arXiv:2605.17937v1 Announce Type: cross Abstract: Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers and limited scalability. While

Balancing Knowledge Distillation for Imbalance Learning with Bilevel Optimization

arXiv:2605.17839v1 Announce Type: cross Abstract: Knowledge distillation transfers knowledge from a high capacity teacher to a compact student using a mixture of hard and soft losses. On imbalanced da

Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity

arXiv:2510.00304v3 Announce Type: replace-cross Abstract: Deep learning models excel in stationary data but struggle in non-stationary environments due to a phenomenon known as loss of plasticity (LoP

Bayesian-Monte Carlo Schedule Updating for Construction Digital Twins: A Probabilistic Framework for Dynamic Project Forecasting

arXiv:2605.17608v1 Announce Type: cross Abstract: Construction projects frequently experience schedule delays and forecasting uncertainty due to variability in labor productivity, material availabilit

Bayesian Networks for Path-Based Sensors: Gathering Information and Path Planning in Communication Denied Environments

arXiv:2605.16673v1 Announce Type: new Abstract: A 'path-based sensor' produces a single observation along a continuous path. For example, a boolean path-based sensor returns a single '1' if an event o

researcharxiv-cs-ro

Beacon: Single-Turn Diagnosis and Mitigation of Latent Sycophancy in Large Language Models

arXiv:2510.16727v2 Announce Type: replace-cross Abstract: Large language models internalize a structural trade-off between truthfulness and obsequious flattery, emerging from reward optimization that

Becoming AI-native is no longer a path to success — it’s an operational prerequisite

The AI-native enterprise isn’t an ideal anymore. Instead, it has become the new competitive baseline. Dell Technologies Inc. has spent nearly three years interrogating that reality from the inside, us

applicationssiliconangle

Agents

Before enterprises can run with agentic AI, they need to learn to walk with their data

Multi-agent orchestration is the destination, but for most enterprises, the road is blocked long before the first agent gets deployed by the quality of the data feeding those systems. As organizations

agentssiliconangle

BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering

arXiv:2605.17435v1 Announce Type: new Abstract: Biomedical question answering often requires decisions from retrieved literature whose relevance, quality, and support for candidate answers are uneven.

researcharxiv-cs-cl

Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations

model-releasesarxiv-cs-ro

arXiv:2605.18059v1 Announce Type: new Abstract: Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving h

Benchmarking inference at scale: coding agents

model-releasestogether-ai-blog

This article presents benchmarking results for AI coding agents evaluated at scale, likely comparing performance metrics such as code generation accuracy, execution success rates, and inference effici

Benchmarking Mythos-Linked Bug Rediscovery

arXiv:2605.17416v1 Announce Type: cross Abstract: Anthropic's April 2026 Mythos materials combine benchmark claims with concrete bug-finding stories across OpenBSD, FreeBSD, Linux, FFmpeg, and browser

Benchmarking Recurrent Event-Based Object Detection for Industrial Multi-Class Recognition on MTevent

model-releasesarxiv-cs-cv

arXiv:2603.21787v2 Announce Type: replace Abstract: Event cameras are attractive for industrial robotics because they provide high temporal resolution, high dynamic range, and reduced motion blur. How

Benchmarking transferability of SSL pretraining to same and different modality segmentation tasks

arXiv:2605.18491v1 Announce Type: new Abstract: Methods: Nine SSL methods spanning four pretext-task families were pretrained from scratch using the same 10{,}412 3D CT scans (1.89~M 2D axial slices)

safetyarxiv-cs-cv

BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation

arXiv:2605.17508v1 Announce Type: cross Abstract: Split Federated Learning (SFL) enables privacy-preserving collaborative training by partitioning models between clients and a server. However, under n

Best-of-Both-Worlds Multi-Dueling Bandits: Unified Algorithms for Stochastic and Adversarial Preferences under Condorcet and Borda Objectives

arXiv:2603.18972v3 Announce Type: replace Abstract: Multi-dueling bandits, where a learner selects m geq 2 arms per round and observes only the winner, arise naturally in many applications including r

researcharxiv-cs-lg

Best Segmentation Buddies for Image-Shape Correspondence

arXiv:2605.18193v1 Announce Type: new Abstract: Finding correspondences is a fundamental and extensively researched problem in computer vision and graphics. In this work, we examine the underexplored

Better Together: Evaluating the Complementarity of Earth Embedding Models

arXiv:2605.18667v1 Announce Type: new Abstract: Earth embedding models transform Earth observation data into embeddings uniquely tied to locations on the Earth's surface. These models are typically ev

Beyond Accuracy: Decomposing the Reasoning Efficiency of LLMs

arXiv:2602.09805v2 Announce Type: replace-cross Abstract: As reasoning LLMs increasingly trade tokens for accuracy through deliberation, search, and self-correction, a single accuracy score can no lon

Beyond Accuracy: Robustness, Interpretability and Expressiveness of EEG Foundation Models

arXiv:2605.17562v1 Announce Type: cross Abstract: EEG foundation models (EEG-FMs) have been evaluated predominantly on clean, in-distribution accuracy, leaving their robustness, interpretability and r

Beyond Catalogue Counts: the Dataset Visibility Asymmetry in Low-Resource Multilingual NLP

arXiv:2605.17442v1 Announce Type: cross Abstract: Multilingual NLP often relies on dataset counts from centralized catalogues to characterize which languages are resource-rich or resource-poor. Howeve

applicationsarxiv-cs-ai

Beyond Compliance: How AI Could Help Creative Writers by Refusing Them

arXiv:2605.16272v1 Announce Type: cross Abstract: Mainstream creativity support design prioritizes compliant AI for seamless writing interactions, but concerns over inappropriate AI reliance highlight

safetyarxiv-cs-ai

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training

arXiv:2509.03403v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves final-answer accuracy on reasoning tasks, but it does not reliably improve reas

Beyond Detection: A Structure-Aware Framework for Scene Text Tracking

model-releasesarxiv-cs-cv

arXiv:2605.17270v1 Announce Type: new Abstract: Modern visual object trackers show impressive results on general targets, yet their performance drops substantially when dealing with scene text. Althou

Beyond Euclidean Prototypes: Spectral Disentanglement and Geodesic Matching for Few-Shot Medical Image Segmentation

arXiv:2605.17904v1 Announce Type: new Abstract: Few-Shot Medical Image Segmentation (FSMIS) aims to delineate novel anatomical targets from one or a few annotated support images, addressing the annota

Beyond Execution: Static-Analysis Rewards and Hint-Conditioned Diffusion RL for Code Generation

arXiv:2605.17174v1 Announce Type: cross Abstract: Reinforcement Learning (RL) is an important paradigm for aligning Diffusion Language Models (DLMs) toward functional correctness in code generation. H

Beyond Geometry: Efficient Topologically-Grounded Navigation in Complex 3D Environments

model-releasesarxiv-cs-ro

arXiv:2605.17302v1 Announce Type: new Abstract: Ground robot navigation in complex 3D environments is often hindered by geometric ambiguity, where non-traversable structures such as furniture share lo

Beyond Imperfect Alternatives with Rulemapping: A Neuro-Symbolic Case Study on Online Hate Speech

arXiv:2605.16280v1 Announce Type: cross Abstract: Automating legal reasoning forces a choice between imperfect alternatives: symbolic systems offer transparency but struggle with ambiguity, whereas ne

applicationsarxiv-cs-ai

Local Ai

Beyond Inference-Time Search: Reinforcement Learning Synthesizes Reusable Solvers

arXiv:2605.18374v1 Announce Type: cross Abstract: Large language models (LLMs) typically approach combinatorial optimization as an inference-time procedure, solving each instance separately through sa

local-aiarxiv-cs-ai

Beyond Linear Superposition: Discovering Climate Features in AI Weather Models with KAN-SAE

arXiv:2605.17493v1 Announce Type: cross Abstract: Deep learning weather prediction models achieve remarkable predictive skill yet remain largely opaque: we know little about how they represent physica

Beyond MMSE: Enhancing PnP Restoration with ProxiMAP

arXiv:2605.16396v1 Announce Type: new Abstract: Plug-and-Play (PnP) methods have become standard tools for solving imaging inverse problems by replacing the intractable maximum a posteriori (MAP) deno

Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification

arXiv:2605.18522v1 Announce Type: cross Abstract: In histopathology, human experts primarily rely on color as a means of enhancing contrast to interpret tissue morphology, whereas machine vision model

Beyond Neural Incompatibility: Cross-Scale Knowledge Transfer in Language Models through Latent Semantic Alignment

model-releasesarxiv-cs-cl

arXiv:2510.24208v2 Announce Type: replace Abstract: Language Models (LMs) encode substantial knowledge in their parameters, yet it remains unclear how to transfer such knowledge in a fine-grained mann

Beyond Patches: Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation

arXiv:2601.01593v2 Announce Type: replace Abstract: Manual font design is an intricate process that transforms a stylistic visual concept into a coherent glyph set. This challenge persists in automate

Beyond Point-Wise Matching: Structural Representation Alignment for Accelerating Diffusion Transformers

model-releasesarxiv-cs-cv

arXiv:2605.16949v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) demonstrate that aligning noisy latent states with well-trained semantic features-as pioneered by Repre

Beyond Policy Optimization: A Data Curation Flywheel for Sparse-Reward Long-Horizon Planning

arXiv:2508.03018v2 Announce Type: replace Abstract: Large Language Reasoning Models have demonstrated remarkable success on static tasks, yet their application to multi-round agentic planning in inter

safetyarxiv-cs-ai

Beyond RLHF: A Unified Theoretical Framework of Alignment

arXiv:2506.01523v2 Announce Type: replace Abstract: Alignment via reinforcement learning from human feedback (RLHF) has become the dominant paradigm for controlling the quality of outputs from large l

safetyarxiv-cs-lg

Beyond Safety Filtering: Control Barrier Function-Informed Reinforcement Learning for Connected and Automated Vehicles

arXiv:2605.16894v1 Announce Type: new Abstract: Reinforcement Learning (RL) uses rewards to guide learning, yet reward design is typically hand-crafted using heuristics that can be difficult to tune.

safetyarxiv-cs-ro

Beyond Scaling: Agents Are Heading to the Edge

arXiv:2605.18535v1 Announce Type: new Abstract: The bottleneck of useful agentic intelligence has shifted from compressing world knowledge into a single model to executing a coordinated system. This p

safetyarxiv-cs-lg

Beyond Sentiment Classification: A Generative Framework for Emotion Intensity Evaluation in Text

arXiv:2605.16613v1 Announce Type: new Abstract: We introduce a novel approach to emotion modeling that shifts the focus from identification to evaluation, addressing the limitations of discrete classi

applicationsarxiv-cs-cl

Beyond Square Roots: Explicit Memory-Efficient Factorization for Multi-Epoch Private Learning

arXiv:2605.18379v1 Announce Type: new Abstract: Correlated-noise mechanisms are among the most promising approaches for improving the utility of differentially private model training, but rigorous gua

researcharxiv-cs-lg