All entries

Can AI Draw Science? A Benchmark for Evaluating Scientific Figure Generation by Text-to-Image and Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2606.28406v1 Announce Type: cross Abstract: Text-to-image and multimodal generative models are increasingly used to produce scientific figures such as mechanism diagrams, experimental-design sch

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Can Fine-Tuning Erase Your Edits? On the Fragile Coexistence of Knowledge Editing and Adaptation

DGX agent

arXiv:2511.05852v4 Announce Type: replace-cross Abstract: Knowledge editing (KE) offers a lightweight alternative to retraining for updating large language models (LLMs). Meanwhile, fine-tuning remain

model-releasesarxiv-cs-ai

30 Jun 2026

Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?

model-releasesarxiv-cs-cl

arXiv:2606.29920v1 Announce Type: new Abstract: Rubric-based scoring has become a widely used paradigm in model evaluation, typically with LLM-as-a-Judge (LaaJ) for rubric scoring. However, the reliab

Can LLMs Hire Fairly? Racial Bias in Resume Screening

model-releasesarxiv-cs-cl

arXiv:2606.28978v1 Announce Type: new Abstract: We audit fourteen mainstream large language models (LLMs) for hiring discrimination using the paired-resume methodology of Kline, Rose, and Walters (202

Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification

model-releasesarxiv-cs-ro

arXiv:2603.19464v2 Announce Type: replace Abstract: Robotic path planning problems are often NP-hard, and practical solutions typically rely on approximation algorithms with provable performance guara

Can LLMs Rank? A Tale of Triads and Triage

arXiv:2606.30412v1 Announce Type: cross Abstract: From housing allocation for households experiencing homelessness to triage in emergency departments, LLMs are increasingly being considered as judges

researcharxiv-cs-ai

Can LLMs Reliably Self-Report Adversarial Prefills, and How?

arXiv:2606.23671v2 Announce Type: replace Abstract: Prior work shows that large language models (LLMs) exhibit introspective capability on benign tasks. We extend the question to safety contexts and e

safetyarxiv-cs-cl

Local Ai

Can Machines Really See Objects in Images? A Study Based on Syntactic Distance and Visual Self-Referential Instances

arXiv:2606.29416v1 Announce Type: cross Abstract: Can a vision model truly see an object, or does it only fit surface-level visual cues? Following Wittgenstein's view that the limits of language are t

local-aiarxiv-cs-ai

Can MLLMs Critique Like Humans? Evaluating Open-Ended Aesthetic Reasoning in Multimodal Large Language Models

arXiv:2606.29689v1 Announce Type: new Abstract: Open-ended aesthetic critique is a challenge for multimodal large language models (MLLMs): unlike multiple-choice aesthetic benchmarks, it has no single

safetyarxiv-cs-cl

Can OCR-VLMs Read Devanagari? A Stress-Test Benchmark and Post-Correction Study

model-releasesarxiv-cs-cl

arXiv:2606.29213v1 Announce Type: new Abstract: OCR systems, ranging from classical engines to specialised OCR vision-language models (OCR-VLMs) and frontier multimodal LLMs, report strong results on

Can regularization based JEPA (e.g. SIGReg) scale and compete with SOTA foundation models (DINO)? Here is the answer: yes and with 10x less …

Can regularization based JEPA (e.g. SIGReg) scale and compete with SOTA foundation models (DINO)? Here is the answer: yes and with 10x less data. VISReg (slight variation of SIGReg) competes with DINO

researchyann-lecun--x

CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluation

arXiv:2606.30430v1 Announce Type: cross Abstract: The increasing connectivity of modern vehicles has made securing in-vehicle communication networks a critical challenge. Intrusion Detection Systems (

researcharxiv-cs-lg

Capability Gates Are Not Authorization: Confused-Deputy Failures in LLM Agent Frameworks

arXiv:2606.28679v1 Announce Type: cross Abstract: Tool-using LLM agents increasingly read untrusted content while holding side-effecting tools such as payments, email, CRM, and infrastructure APIs, ye

CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training

arXiv:2603.23559v2 Announce Type: replace-cross Abstract: GUI agents are rapidly shifting from multi-module pipelines to end-to-end, native vision-language models (VLMs) that perceive raw screenshots

CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation

arXiv:2603.06866v3 Announce Type: replace Abstract: Developing autonomous mobile robot systems typically requires either extensive, platform-specific data collection or relies on simplified abstractio

agentsarxiv-cs-ro

CAREBench: A Child-Safety Risk Benchmark for Language Models

model-releasesarxiv-cs-lg

arXiv:2606.29685v1 Announce Type: new Abstract: How can we evaluate whether frontier AI systems recognize child-safety risks before they escalate into explicit harm? Existing child safety evaluations

CaresAI at CT-DEB26: Detecting Dosing Errors In Clinical Trials Using Domain-Specific Transformer Embeddings and Classification Models

arXiv:2606.30236v1 Announce Type: new Abstract: Medication errors, particularly dosing errors in clinical trials (CT), can lead to patient harm, adverse drug events and worse patient outcomes. Dosing

safetyarxiv-cs-cl

Carolina Guide: A Multi-Agent RAG System with Institutional Guardrails for Academic Policy Assistance

arXiv:2606.28360v1 Announce Type: cross Abstract: University students often struggle to navigate complex academic policies, leading to advising bottlenecks and delayed access to critical information.

safetyarxiv-cs-ai

CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models

model-releasesarxiv-cs-ai

arXiv:2501.14940v4 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with human values is essential for their safe deployment and widespread adoption. Current LLM safety ben

Categorize Early, Integrate Late: Divergent Processing Strategies in Automatic Speech Recognition

arXiv:2601.06972v2 Announce Type: replace Abstract: In speech language modeling, two architectures dominate the frontier: the Transformer and the Conformer. However, it remains unknown whether their c

researcharxiv-cs-cl

Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch

arXiv:2606.28815v1 Announce Type: cross Abstract: Mathswitch is an open-source project that imports mathematical concept records from sources such as Wikidata, Wikipedia, MathWorld, Encyclopedia of Ma

safetyarxiv-cs-ai

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework

model-releasesarxiv-cs-ai

arXiv:2406.08311v3 Announce Type: replace-cross Abstract: Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate

CaveAgent: Transforming LLMs into Stateful Runtime Operators

arXiv:2601.01569v4 Announce Type: replace Abstract: LLM-based agents are increasingly capable of complex task execution, yet current agentic systems remain constrained by text-centric paradigms that s

Local Ai

CCRC: A Change-Aware Captioning and Reasoning Chain for Image Change Captioning and Segmentation

arXiv:2606.28724v1 Announce Type: cross Abstract: Understanding and localizing subtle changes between paired images is critical for tasks such as surveillance and image editing. However, traditional I

local-aiarxiv-cs-ai

CellDETR: A Detection-Guided Framework for Scalable Cell Representation Learning from Histopathology Images

arXiv:2606.29463v1 Announce Type: new Abstract: Recent advances in pathology foundation models have substantially improved patch and slide level representation learning from whole-slide images (WSIs).

researcharxiv-cs-cv

Tools

Certified token billionaire. Having a blast at AIE, fantastic conf @swyx

The post references someone attending AIE (likely an AI or tech conference) and describes having a positive experience, with 'certified token billionaire' appearing to be either a humorous self-descri

toolsswyx--x

Chamber geometry and specification numbers of Boolean threshold functions

arXiv:2606.29477v1 Announce Type: cross Abstract: The specification number sigma_n(f) of a Boolean threshold function f on n variables is the least number of points whose f-values determine f uniquely

researcharxiv-cs-lg

Applications

Character Recognition of Nepali Number Plate

arXiv:2606.28946v1 Announce Type: new Abstract: This paper presents a robust Automatic Number Plate Recognition (ANPR) system tailored for Nepali license plates written in Devanagari script. In this p

applicationsarxiv-cs-cv

Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem

arXiv:2606.29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combin

safetyarxiv-cs-ai

Local Ai

Characterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and Localization

arXiv:2606.30226v1 Announce Type: new Abstract: Hessian spectral properties are a standard tool in analysing neural-network training, with eigenvalues linked to sharpness, generalization, and optimiza

local-aiarxiv-cs-lg

Tools

@charlieholtz preach! “Factories” is a depressing vision of the future, metaphors matter

This post discusses how the metaphor of 'factories' for AI systems presents a pessimistic framing of the future, arguing that the language and analogies we use to describe AI development shape our per

toolsswyx--x

Child-Centric Voice Anonymization in Single and Multi-Speaker Speech via Domain-Adapted SSL Models

arXiv:2606.29897v1 Announce Type: cross Abstract: Voice anonymization aims to protect speaker identity while preserving linguistic content and speech usability. However, most anonymization systems are

researcharxiv-cs-ai

China’s Meituan open-sources massive LongCat-2.0 AI model, saying it was trained on domestic chips

model-releasessiliconangle

Beijing, China-based Meituan Inc. today debuted its next-generation LongCat-2.0 open-source large language model, stating that the company trained the 1.6-trillion-parameter model on domestic Chinese

Choose Your Agent: Tradeoffs in Adopting AI Advisors, Coaches, and Delegates in Multi-Party Negotiation

arXiv:2602.12089v3 Announce Type: replace-cross Abstract: As AI usage becomes more prevalent in social contexts, understanding agent-user interaction is critical to designing systems that imp rove bot

Chronos: A Physics-Informed Full-History Framework for Non-Markovian Long-Horizon Manipulation

arXiv:2606.30318v1 Announce Type: new Abstract: General-purpose robot policies should be modeled as dynamical systems, yet many VLA and generative imitation policies still rely on present observations

safetyarxiv-cs-ro

Tutorials

CLARity: Reasoning Consistency Alone Can Teach Reinforced Experts

arXiv:2510.09278v2 Announce Type: replace-cross Abstract: Training expert LLMs in domains with scarce data is difficult, often relying on multiple-choice questions (MCQs). However, standard outcome-ba

tutorialsarxiv-cs-ai

Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration

arXiv:2606.30246v1 Announce Type: new Abstract: Existing autonomous research agents can support parts of the research process, but most systems still treat research as either an isolated assistant tas

Claude Desktop is now available on Linux (Ubuntu and Debian) in beta. Alongside the browser and terminal, you now get a first-class desktop …

Claude Desktop is now available on Linux (Ubuntu and Debian) in beta. Alongside the browser and terminal, you now get a first-class desktop experience with Claude Code, Claude Cowork, and chat on all

model-releasesthariq--x

Claude Science is Anthropic’s newest flagship product

model-releasesmit-tech-review

At an event for pharmaceutical executives, biotech founders, and researchers on Tuesday, Anthropic announced Claude Science, a major new product intended to support scientific research in the same way

Claude Sonnet 5 costs 2 per 1M input tokens and 10 per 1M output tokens through August 31, after which prices rise to 3 and 15, respectively (Zac Hall/9to5Mac)

Zac Hall / 9to5Mac: Claude Sonnet 5 costs 2 per 1M input tokens and 10 per 1M output tokens through August 31, after which prices rise to 3 and 15, respectively — Anthropic is upgrading Claude Sonnet,

model-releasestechmeme

Claude Sonnet 5 is now available in Cursor. On CursorBench, it's a meaningful step up from Sonnet 4.6: 57% vs. 49%.

Claude Sonnet 5 is now available as a model option in the Cursor code editor. On CursorBench, Sonnet 5 achieves a 57% score compared to Sonnet 4.6's 49%, representing a meaningful performance improvem

model-releasescursor--x

Claude Sonnet 5 is now available in Devin Desktop and Devin CLI. Sonnet 5 pairs frontier-level coding performance with a more affordable pri…

model-releasescognition-ai--x

Claude Sonnet 5 has been integrated into Devin Desktop and Devin CLI, offering advanced coding capabilities at a more competitive price point than previous models. This release represents an update to

Claude Sonnet 5 is now available in Perplexity for Pro and Max subscribers. You can also select it as an orchestrator model in Computer.

model-releasesperplexity--x

Claude Sonnet 5 is now available for use in Perplexity, accessible to Pro and Max tier subscribers. Users can also select Claude Sonnet 5 as an orchestrator model within Perplexity's Computer feature,

Claude Sonnet 5 now available on Vercel AI Gateway

model-releasesvercel-blog

Claude Sonnet 5 is now accessible through Vercel's AI Gateway, enabling developers to integrate Anthropic's latest language model into their applications via Vercel's unified API platform. This integr

Hardware

CLEAR-MoE: Shared-Basis Expert Extraction from Frozen Vision Transformers via Calibration-Driven Layer Selection

arXiv:2606.28516v1 Announce Type: new Abstract: We present CLEAR-MoE, a four-phase post-training pipeline that converts a frozen pretrained Vision Transformer (ViT) into a sparse Mixture-of-Experts (M

hardwarearxiv-cs-cv

Clearer Sight, Fewer Lies: Oriented Pickup Preference Optimization for Multimodal Hallucination Mitigation

arXiv:2606.29805v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are prone to hallucination as their generation preferences are insufficiently calibrated to visual evidence, ca

safetyarxiv-cs-cv

CLIMP: Contrastive Language-Image Mamba Pretraining

arXiv:2601.06891v2 Announce Type: replace Abstract: Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and

researcharxiv-cs-cv

Clinical Reasoning Graphs: Structured Evaluation of LLM Diagnostic Reasoning Reveals Competence Without Consistency

arXiv:2606.29876v1 Announce Type: cross Abstract: Modern large language models (LLMs) reach 60-70% diagnostic accuracy on complex clinical case benchmarks, but accuracy alone cannot distinguish stable

researcharxiv-cs-ai