model releases

CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

arXiv:2509.20374v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated strong performance across general NLP tasks, but their utility in automating numerical experime

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Channel Adaptation for EEG Foundation Models: A Systematic Benchmark Across Architectures, Tasks, and Training Regimes

DGX agent

arXiv:2604.23091v1 Announce Type: new Abstract: Scaling EEG foundation models requires pooling data across heterogeneous electrode montages, a prerequisite both for larger pretraining corpora and for

model-releasesarxiv-cs-lg

28 Apr 2026

Chinese-SkillSpan: A Span-Level Dataset for ESCO-Aligned Competency Extraction from Chinese Job Ads

arXiv:2604.23009v1 Announce Type: new Abstract: Job Skill Named Entity Recognition (JobSkillNER) aims to automatically extract key skill information from large-scale job posting data, which is importa

Citation-Driven Multi-View Training for Patent Embeddings: QaECTER and Sophia-Bench

arXiv:2604.22897v1 Announce Type: cross Abstract: Patent retrieval underpins critical decisions in innovation, examination, and IP strategy, yet progress has been hampered by the absence of benchmarks

CiteAudit: You Cited It, But Did You Read It? A Benchmark for Verifying Scientific References in the LLM Era

arXiv:2602.23452v2 Announce Type: replace Abstract: Scientific research relies on accurate citation for attribution and integrity, yet large language models (LLMs) introduce a new risk: fabricated ref

Claude can now plug directly into Photoshop, Blender, and Ableton

model-releasesthe-verge-ai

Anthropic has launched a set of connectors for Claude that allow the AI chatbot to tap into popular creative software, including Adobe's Creative Cloud apps, Affinity, Blender, Ableton, Autodesk, and

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

arXiv:2604.23781v1 Announce Type: new Abstract: Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surroundi

ClawTrace: Cost-Aware Tracing for LLM Agent Skill Distillation

arXiv:2604.23853v1 Announce Type: new Abstract: Skill-distillation pipelines learn reusable rules from LLM agent trajectories, but they lack a key signal: how much each step costs. Without per-step co

ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis

arXiv:2604.16922v2 Announce Type: replace Abstract: Climate research is pivotal for mitigating global environmental crises, yet the accelerating volume of multi-scale datasets and the complexity of an

CLIN-LLM: A Safety-Constrained Hybrid Framework for Clinical Diagnosis and Treatment Generation

arXiv:2510.22609v2 Announce Type: replace Abstract: Accurate symptom-to-disease classification and clinically grounded treatment recommendations remain challenging, particularly in heterogeneous patie

Clotho: Measuring Task-Specific Pre-Generation Test Adequacy for LLM Inputs

model-releasesarxiv-cs-lg

arXiv:2509.17314v3 Announce Type: replace-cross Abstract: Software increasingly relies on the emergent capabilities of Large Language Models (LLMs), from natural language understanding to program anal

Comparative Study of Weighted and Coupled Second- and Fourth-Order PDEs for Image Despeckling in Grayscale, Color, SAR, and Ultrasound

arXiv:2604.23612v1 Announce Type: new Abstract: Partial Differential Equation (PDE)-based approaches have gained significant attention in image despeckling due to their strong capability to preserve s

Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility, Cost, and Bottlenecks in Multi-Agent Workflows

arXiv:2604.22820v1 Announce Type: cross Abstract: Long-horizon tool-using tasks sometimes benefit from revisiting earlier subtasks for recovery and exploration, but added multi-agent workflow flexibil

Complexity of Linear Regions in Self-supervised Deep ReLU Networks

arXiv:2604.24393v1 Announce Type: cross Abstract: There has been growing interest in studying the complexity of Rectified Linear Unit (ReLU) based activation networks. Recent work investigates the evo

ComplianceNLP: Knowledge-Graph-Augmented RAG for Multi-Framework Regulatory Gap Detection

arXiv:2604.23585v1 Announce Type: new Abstract: Financial institutions must track over 60,000 regulatory events annually, overwhelming manual compliance teams; the industry has paid over USD 300 billi

Constraint-Based Analysis of Reasoning Shortcuts in Neurosymbolic Learning

arXiv:2604.23377v1 Announce Type: new Abstract: Neurosymbolic systems can satisfy logical constraints during learning without achieving the intended concept-label correspondence; this is a problem kno

Context management in agent harnesses: memory, files, and subagents

A version of this article originally appeared on X. Every agent harness runs into the same limit: the context window is too small for everything the model might want to remember.... The post Context m

model-releasesarize-ai

CorpusQA: A 10 Million Token Benchmark for Corpus-Level Analysis and Reasoning

arXiv:2601.14952v2 Announce Type: replace-cross Abstract: While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largel

Cortex-Inspired Continual Learning: Unsupervised Instantiation and Recovery of Functional Task Networks

arXiv:2604.24637v1 Announce Type: cross Abstract: Block-sequential continual learning demands that a single model both protect prior solutions from catastrophic forgetting and efficiently infer at inf

Coverage-Based Calibration for Post-Training Quantization via Weighted Set Cover over Outlier Channels

model-releasesarxiv-cs-lg

arXiv:2604.24008v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) compresses large language models to low bit-widths using a small calibration set, and its quality depends strongly on w

CRISP: Persistent Concept Unlearning via Sparse Autoencoders

arXiv:2508.13650v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preser

CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks

arXiv:2510.17687v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak att

CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation

arXiv:2604.24001v1 Announce Type: new Abstract: The evaluation of generated reports remains a critical challenge in Computed Tomography (CT) report generation, due to the large volume of text, the div

CUB: Benchmarking Context Utilisation Techniques for Language Models

arXiv:2505.16518v3 Announce Type: replace-cross Abstract: Incorporating external knowledge is crucial for knowledge-intensive tasks, such as question answering and fact checking. However, language mod

DARC-CLIP: Dynamic Adaptive Refinement with Cross-Attention for Meme Understanding

arXiv:2604.23214v1 Announce Type: new Abstract: Memes convey meaning through the interaction of visual and textual signals, often combining humor, irony, and offense in subtle ways. Detecting harmful

DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting

arXiv:2604.23968v1 Announce Type: cross Abstract: Accurate time series forecasting in scientific domains such as climate modeling, physiological monitoring, and energy systems benefits from both compe

Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring

arXiv:2604.24236v1 Announce Type: cross Abstract: The escalating climate crisis and ecosystem degradation demand intelligent, low-cost sensors capable of robust, long-term monitoring in real-world env

DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining

arXiv:2604.23054v1 Announce Type: cross Abstract: Predicting the outcomes of prospective clinical trials remains a major challenge for large language models. Prior work has shown that both traditional

DeepSeek V4-Pro on Fireworks. Zoooooom.

model-releasesfireworks-ai--x

DeepSeek V4-Pro is now available on the Fireworks AI platform, likely offering accelerated inference speeds ('Zoooooom' suggests performance optimization). This deployment enables users to access Deep

DeepTaxon: An Interpretable Retrieval-Augmented Multimodal Framework for Unified Species Identification and Discovery

arXiv:2604.24029v1 Announce Type: cross Abstract: Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis

arXiv:2604.24703v1 Announce Type: cross Abstract: Large language models are widely used for code generation, yet they rely on an implicit assumption that the task descriptions are sufficiently detaile

Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing

arXiv:2604.24162v1 Announce Type: cross Abstract: Defending against backdoor attacks in large language models remains a critical practical challenge. Existing defenses mitigate these threats but typic

Deploy DINO with Many-to-Many Association

arXiv:2604.23670v1 Announce Type: new Abstract: Motivated by the limited generalization of supervised image matching models to unseen image domains, we explore the zero-shot deployment of DINO feature

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

arXiv:2406.10185v2 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging r

DGHMesh: A Large-scale Dual-radar mmWave Dataset and Generalization-focused Benchmark for Human Mesh Reconstruction

arXiv:2604.22827v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar has shown great potential for contactless, privacy-preserving, and robust human sensing, yet existing mmWave-based human

did a whole section on claude design because i'm loving it (like this deck) under the hood, it's claude code with an opinionated ontology on…

model-releasesyohei-nakajima--x

did a whole section on claude design because i'm loving it (like this deck) under the hood, it's claude code with an opinionated ontology on both input (typography, logos, etc.) and output (slides, de

Differentiable Faithfulness Alignment for Cross-Model Circuit Transfer

arXiv:2604.24302v1 Announce Type: new Abstract: Mechanistic interpretability has made it possible to localize circuits underlying specific behaviors in language models, but existing methods are expens

Diffusion Templates: A Unified Plugin Framework for Controllable Diffusion

arXiv:2604.24351v1 Announce Type: cross Abstract: Controllable diffusion methods have substantially expanded the practical utility of diffusion models, but they are typically developed as isolated, ba

Distilling Self-Consistency into Verbal Confidence: A Pre-Registered Negative Result and Post-Hoc Rescue on Gemma 3 4B

arXiv:2604.24070v1 Announce Type: cross Abstract: Small instruct-tuned LLMs produce degenerate verbal confidence under minimal elicitation: ceiling rates above 95%, near-chance Type-2 AUROC, and Inval

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models

arXiv:2604.22822v1 Announce Type: cross Abstract: Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verifica

Do Quantum Transformers Help? A Systematic VQC Architecture Comparison on Tabular Benchmarks

arXiv:2604.23931v1 Announce Type: cross Abstract: Variational quantum circuits (VQCs) are a leading approach to quantum machine learning on near-term devices, yet it remains unclear which circuit arch

Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening

model-releasesarxiv-cs-lg

arXiv:2604.23385v1 Announce Type: new Abstract: Transthoracic echocardiography is the reference standard for confirming structural heart disease (SHD), but first-line screening is limited by cost, wor

Domain Fine-Tuning vs. Retrieval-Augmented Generation for Medical Multiple-Choice Question Answering: A Controlled Comparison at the 4B-Parameter Scale

arXiv:2604.23801v1 Announce Type: new Abstract: Practitioners deploying small open-weight large language models (LLMs) for medical question answering face a recurring design choice: invest in a domain

Don't just reset Codex rate limits for fun, it costs money. Don't just reset Codex rate limits for fun, it costs money. ... but the vibes ar…

model-releasessam-altman--x

Don't just reset Codex rate limits for fun, it costs money. Don't just reset Codex rate limits for fun, it costs money. ... but the vibes are good ... I have reset Codex rate limits for ALL paid plans

Don't Make the LLM Read the Graph: Make the Graph Think

arXiv:2604.23057v1 Announce Type: new Abstract: We investigate whether explicit belief graphs improve LLM performance in cooperative multi-agent reasoning. Through 3,000+ controlled trials across four

Don't Pause! Every prediction matters in a streaming video

arXiv:2604.24317v1 Announce Type: new Abstract: Streaming video models should respond the moment an event unfolds, not after the moment has passed. Yet existing online VideoQA benchmarks remain largel

DreamAudio: Customized Text-to-Audio Generation with Diffusion Models

arXiv:2509.06027v3 Announce Type: replace-cross Abstract: With the development of large-scale diffusion-based and language-modeling-based generative models, impressive progress has been achieved in te

DRIFT: Transferring Reasoning Priors for Efficient MLLM Fine-Tuning

arXiv:2510.15050v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have made rapid progress, yet their reasoning ability often lags behind strong text-only LLMs. Bridging thi