All entries

Congestion-Aware Dynamic Axonal Delay for Spiking Neural Networks

model-releasesarxiv-cs-lg

arXiv:2605.01291v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) are widely regarded as an energy-efficient paradigm for modeling and processing temporal and event-driven information. In

Constructing Interpretable Features from Compositional Neuron Groups

DGX agent

arXiv:2506.10920v2 Announce Type: replace Abstract: A central goal for mechanistic interpretability has been to identify the right units of analysis in large language models (LLMs) that causally expla

model-releasesarxiv-cs-cl

5 May 2026

ContextualJailbreak: Evolutionary Red-Teaming via Simulated Conversational Priming

arXiv:2605.02647v1 Announce Type: new Abstract: Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety alignment and elicit harmful responses. A growing body of work sh

Continual Few-shot Adaptation for Synthetic Fingerprint Detection

arXiv:2603.14632v2 Announce Type: replace Abstract: The quality and realism of synthetically generated fingerprint images have increased significantly over the past decade fueled by advancements in ge

Continual Learning of Feedback-based Molecular Communication

arXiv:2605.01020v1 Announce Type: new Abstract: This paper proposes and evaluates a new performance estimation method that leverages continual learning (CL) algorithms to carry out sequential simulati

tutorialsarxiv-cs-lg

Continuous quantification of viral plaque dynamics using ultra-large-area label-free imaging enables rapid antiviral susceptibility testing

arXiv:2605.01738v1 Announce Type: cross Abstract: The plaque reduction assay (PRA) remains the gold standard for antiviral susceptibility testing, evaluating drug potency by measuring reductions in pl

Continuous Temporal Representations of Event-Based Signals via Interference-Based Wave Modeling

arXiv:2605.01270v1 Announce Type: new Abstract: Spatio-temporal signals arising from event-driven biological processes, such as surface electromyography (sEMG), exhibit asynchronous and highly structu

researcharxiv-cs-lg

Contrastive Residual Energy Test-time Adaptation

arXiv:2505.19607v2 Announce Type: replace Abstract: Test-time adaptation (TTA) enhances model robustness by enabling adaptation to target distributions that differ from training distributions, improvi

safetyarxiv-cs-lg

Control Reinforcement Learning: Interpretable Token-Level Steering of LLMs via Sparse Autoencoder Features

arXiv:2602.10437v3 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) decompose language model activations into interpretable features, but existing methods reveal only which features a

Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs

model-releasesarxiv-cs-ai

arXiv:2505.20948v3 Announce Type: replace Abstract: Abductive reasoning in knowledge graphs aims to generate plausible logical hypotheses from observed entities, with broad applications in areas such

Controlled Paraphrase Geometry in Sentence Embedding Space: Local Manifold Modeling and Latent Probing

arXiv:2605.01073v1 Announce Type: new Abstract: The paper studies the local geometry of embedding clouds induced by controlled local classes of semantically close sentences. The central question is ho

researcharxiv-cs-cl

Coopetition-Gym v1: A Formally Grounded Platform for Mixed-Motive Multi-Agent Reinforcement Learning under Strategic Coopetition

model-releasesarxiv-cs-lg

arXiv:2605.02063v1 Announce Type: cross Abstract: We present Coopetition-Gym v1, a benchmark platform for mixed-motive multi-agent reinforcement learning under strategic coopetition. The platform comp

CoRAL: Contact-Rich Adaptive LLM-based Control for Robotic Manipulation

arXiv:2605.02600v1 Announce Type: new Abstract: While Large Language Models (LLMs) and Vision-Language Models (VLMs) demonstrate remarkable capabilities in high-level reasoning and semantic understand

applicationsarxiv-cs-ro

Correlates of Image Memorability in Vision Encoders: Activations, Attention Entropy, Patch Uniformity and Autoencoder Losses

arXiv:2509.01453v2 Announce Type: replace Abstract: Images vary in how memorable they are to humans. Inspired by findings from cognitive science and computer vision, we explore correlates of image mem

CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features

arXiv:2508.12535v3 Announce Type: replace Abstract: Sparse Autoencoders (SAEs) can extract interpretable features from large language models (LLMs) without supervision. However, their effectiveness in

CoSpaDi: Compressing LLMs via Calibration-Guided Sparse Dictionary Learning

arXiv:2509.22075v5 Announce Type: replace Abstract: Post-training compression of large language models (LLMs) often relies on low-rank weight approximations that represent each column of the weight ma

Counting as a minimal probe of language model reliability

arXiv:2605.02028v1 Announce Type: new Abstract: Large language models perform strongly on benchmarks in mathematical reasoning, coding and document analysis, suggesting a broad ability to follow instr

researcharxiv-cs-cl

Industry

Coupang reports Q1 revenue up 8% YoY to 8.5B and a net loss of 266M following a 2025 Korean customer data breach, its largest loss since Q4 2021 (The Korea Herald)

The Korea Herald: Coupang reports Q1 revenue up 8% YoY to 8.5B and a net loss of 266M following a 2025 Korean customer data breach, its largest loss since Q4 2021 — US-listed e-commerce giant Coupang

industrytechmeme

CP-SynC: Multi-Agent Zero-Shot Constraint Modeling in MiniZinc with Synthesized Checkers

arXiv:2605.01675v1 Announce Type: cross Abstract: Constraint Programming (CP) is a powerful paradigm for solving combinatorial problems, yet translating natural language problem descriptions into exec

CRC-Screen: Certified DNA-Synthesis Hazard Screening Under Taxonomic Shift

arXiv:2605.00074v1 Announce Type: cross Abstract: DNA-synthesis providers screen incoming orders by searching the requested sequence against curated hazard lists. We show that this baseline collapses

researcharxiv-cs-ai

Creating and Evaluating Figurative Language Dataset for Sindhi

arXiv:2605.01323v1 Announce Type: new Abstract: In this article, we introduce SiNFluD, a novel benchmark dataset for Sindhi figurative language classification. We first collect raw text from various b

CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing

arXiv:2602.15823v2 Announce Type: replace Abstract: A central challenge in large language model (LLM) editing is capability preservation: methods that successfully change targeted behavior can quietly

researcharxiv-cs-lg

Industry

CRM software company Freshworks said it plans to cut 11% of its workforce, or ~500 jobs, as it deals with AI's impact; FRSH has dropped ~26% in 2026 (Anhata Rooprai/Reuters)

Anhata Rooprai / Reuters: CRM software company Freshworks said it plans to cut 11% of its workforce, or ~500 jobs, as it deals with AI's impact; FRSH has dropped ~26% in 2026 — Freshworks (FRSH.O) sai

industrytechmeme

Cross-Domain Adversarial Augmentation: Stabilizing GANs for Medical and Handwriting Data Scarcity

arXiv:2605.01815v1 Announce Type: new Abstract: Generative Adversarial Networks (GANs) offer a pragmatic route to mitigate data scarcity in vision tasks. We study generative augmentation across two lo

Cross-Language Learning within Arabic Script for Low-Resource HTR

model-releasesarxiv-cs-cv

arXiv:2605.02089v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) under limited labeled data remains a challenging problem, particularly for Arabic-script languages. Although modern s

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers

arXiv:2510.22555v2 Announce Type: replace-cross Abstract: Graph Neural Networks(GNNs) are vulnerable to backdoor attacks, where adversaries implant malicious triggers to manipulate model predictions.

applicationsarxiv-cs-lg

Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping

arXiv:2605.02153v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mappi

Cross-Scale Pretraining: Enhancing Self-Supervised Learning for Low-Resolution Satellite Imagery for Semantic Segmentation

arXiv:2601.12964v2 Announce Type: replace Abstract: Self-supervised pretraining in remote sensing is mostly done using mid-spatial resolution (MR) image datasets due to their high availability. Given

tutorialsarxiv-cs-cv

Industry

Crypto exchange Bullish agrees to acquire Equiniti, a UK-based financial services outsourcing business, from Siris Capital in a $4.2B deal, set to close in 2027 (Emily Nicolle/Bloomberg)

Emily Nicolle / Bloomberg: Crypto exchange Bullish agrees to acquire Equiniti, a UK-based financial services outsourcing business, from Siris Capital in a 4.2B deal, set to close in 2027 — Bullish agr

industrytechmeme

CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint

arXiv:2605.01479v1 Announce Type: new Abstract: Latent-based diffusion model watermarking embeds watermarks into generated images' latent space to enable content attribution, offering a training-free

CUE: Concept-Aware Multi-Label Expansion to Mitigate Concept Confusion in Long-Tailed Learning

arXiv:2605.01309v1 Announce Type: new Abstract: Long-tailed distributions are common in real-world recognition tasks, where a few head classes have many samples while most tail classes have very few.

safetyarxiv-cs-cv

Tools

Cursor can now automatically fix CI failures. Set up always-on agents that monitor GitHub, investigate root causes, and open PRs with fixes.

Cursor has introduced an automated CI failure resolution feature that uses always-on agents to monitor GitHub repositories, analyze build failures, and automatically generate pull requests with fixes.

toolscursor--x

Cut-In Gap Acceptance Toward Autonomous vs. Human-Driven Vehicles: Evidence from the Waymo Open Motion Dataset

arXiv:2605.01485v1 Announce Type: new Abstract: Autonomous vehicles (AVs) are widely known to follow conservative, rule-based motion policies that surrounding drivers can learn to anticipate. A direct

safetyarxiv-cs-ro

CycleRL: Sim-to-Real Deep Reinforcement Learning for Robust Autonomous Bicycle Control

arXiv:2603.15013v2 Announce Type: replace Abstract: Autonomous bicycles offer a promising agile solution for urban mobility and last-mile logistics. However, conventional control strategies often stru

safetyarxiv-cs-ro

CyclicJudge: Mitigating Judge Bias Efficiently in LLM-based Evaluation

arXiv:2603.01865v3 Announce Type: replace Abstract: LLM-as-judge evaluation has become standard practice for open-ended model assessment; however, judges exhibit systematic biases that cannot be avera

Data-Driven, Geometry-Aware Optimal-Transport Calibration of Flavor Tagger

arXiv:2605.01363v1 Announce Type: cross Abstract: Flavor-tagging calibrations are often provided either as scale factors measured at a finite set of working points or as binned corrections to a chosen

tutorialsarxiv-cs-lg

Tools

datasette-llm 0.1a7

Release: datasette-llm 0.1a7 Mechanism for configuring default options for specific models. Part of Datasette's evolving support mechanism for plugins that use LLMs. It's now possible to configure a m

toolssimon-willison

datasette-referrer-policy 0.1

model-releasessimon-willison

Release: datasette-referrer-policy 0.1 The OpenStreetMap tiles on the Datasette global-power-plants demo weren't displaying correctly. This turned out to be caused by two bugs. The first is that the C

🚀 Day-0 MTP support for Gemma4 now available at vLLM with ready-to-use docker image! ⚡️Enjoy up to 3x faster decoding performance to superc…

model-releasesjeremy-howard--x

🚀 Day-0 MTP support for Gemma4 now available at vLLM with ready-to-use docker image! ⚡️Enjoy up to 3x faster decoding performance to supercharge your development with zero quality degradation! Check o

DBLP: Phase-Aware Bounded-Loss Transport for Burst-Resilient Distributed ML Training

model-releasesarxiv-cs-lg

arXiv:2605.01989v1 Announce Type: new Abstract: Distributed machine learning (ML) training has become a necessity with the prevalence of billion to trillion-parameter-scale models. While prior work ha

Decision Boundary-aware Generation for Long-tailed Learning

arXiv:2605.01468v1 Announce Type: new Abstract: Long-tailed data bias decision boundaries toward head classes and degrade tail class accuracy. Diffusion-based generative augmentation address this prob

safetyarxiv-cs-cv

Decision-Focused Learning via Tangent-Space Projection of Prediction Error

arXiv:2605.01361v1 Announce Type: new Abstract: Decision-Focused Learning (DFL) trains predictors to improve downstream decision quality, but computing regret gradients typically requires differentiat

applicationsarxiv-cs-lg

Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation

arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste

Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation

model-releasesarxiv-cs-cv

arXiv:2605.01448v1 Announce Type: cross Abstract: Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge f

Decouple and Cache: KV Cache Construction for Streaming Video Understanding

arXiv:2605.01858v1 Announce Type: new Abstract: Streaming video understanding requires processing unbounded video streams with limited memory and computation, posing two key challenges. First, continu

tutorialsarxiv-cs-cv

Deep learning-based pavement performance modeling using multiple distress indicators and road work history

arXiv:2605.01914v1 Announce Type: new Abstract: The deterioration of pavement is a complex and dynamic process determined by different factors including material, environment, design, and some other u

applicationsarxiv-cs-lg

Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals

arXiv:2605.00849v1 Announce Type: cross Abstract: Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant

researcharxiv-cs-lg

Deep neural networks with Fisher vector encoding for medical image classification

model-releasesarxiv-cs-cv

arXiv:2605.01667v1 Announce Type: new Abstract: Orderless encoding methods have shown to improve Convolutional Neural Networks (CNNs) for image classification in the context of limited availability of