Search: “models”

Assessment Design in the AI Era: A Method for Identifying Items Functioning Differentially for Humans and Chatbots

model-releasesarxiv-cs-ai

arXiv:2603.23682v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) in education raises profound challenges for assessment design. To adapt assessments to the

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Model Releases

ChatSVA: Bridging SVA Generation for Hardware Verification via Task-Specific LLMs

DGX agent

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

model-releasesarxiv-cs-ai

17 Apr 2026

Class Unlearning via Depth-Aware Removal of Forget-Specific Directions

arXiv:2604.15166v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted knowledge from a trained model without the cost of retraining from scratch. In class unlearning, however, red

Comparison of Modern Multilingual Text Embedding Techniques for Hate Speech Detection Task

arXiv:2604.14907v1 Announce Type: new Abstract: Online hate speech and abusive language pose a growing challenge for content moderation, especially in multilingual settings and for low-resource langua

Create Expert Content: Deploying a Multi-Agent System with Terraform and Cloud Run

model-releasesgoogle-cloud-ai

In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by

Local Ai

DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA

arXiv:2511.22521v2 Announce Type: replace Abstract: Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex doc

local-aiarxiv-cs-cv

Don't Retrieve, Navigate: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG

arXiv:2604.14572v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds LLM responses in external evidence but treats the model as a passive consumer of search results: it never

Evolving Media CDN for the world’s most demanding broadcast and streaming workloads

model-releasesgoogle-cloud-ai

Editor’s note: In this post, we share joint insights from Raj Gulani, Director of Product Management for Network Experiences, and Dan Rayburn, Industry analyst with 30-plus years of experience coverin

Federated Breast Cancer Detection Enhanced by Synthetic Ultrasound Image Augmentation

arXiv:2506.23334v3 Announce Type: replace-cross Abstract: Federated learning enables collaborative training of deep learning models across institutions without sharing sensitive patient data. However,

researcharxiv-cs-cv

Tutorials

Federated Multi-Task Clustering

arXiv:2512.22897v3 Announce Type: replace Abstract: Spectral clustering has emerged as one of the most effective clustering algorithms due to its superior performance. However, most existing models ar

tutorialsarxiv-cs-lg

From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures

arXiv:2601.02997v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel in program synthesis, yet their capacity for neural architecture design -- balancing syntactic reliability,

Applications

Graph-Based Fraud Detection with Dual-Path Graph Filtering

arXiv:2604.14235v1 Announce Type: new Abstract: Fraud detection on graph data can be viewed as a demanding task that requires distinguishing between different types of nodes. Because graph neural netw

applicationsarxiv-cs-lg

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning

arXiv:2604.15148v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to perform search-augmented reasoning. However, existin

safetyarxiv-cs-cl

Learning Adaptive Reasoning Paths for Efficient Visual Reasoning

arXiv:2604.14568v1 Announce Type: cross Abstract: Visual reasoning models (VRMs) have recently shown strong cross-modal reasoning capabilities by integrating visual perception with language reasoning.

safetyarxiv-cs-cl

Leveraging graph neural networks and mobility data for COVID-19 forecasting

arXiv:2501.11711v2 Announce Type: replace Abstract: The COVID-19 pandemic has claimed millions of lives, spurring the development of diverse forecasting models. In this context, the true utility of co

LLM Predictive Scoring and Validation: Inferring Experience Ratings from Unstructured Text

arXiv:2604.14321v1 Announce Type: new Abstract: We tasked GPT-4.1 to read what baseball fans wrote about their game-day experience and predict the overall experience rating each fan gave on a 0-10 sur

MambaSL: Exploring Single-Layer Mamba for Time Series Classification

arXiv:2604.15174v1 Announce Type: new Abstract: Despite recent advances in state space models (SSMs) such as Mamba across various sequence domains, research on their standalone capacity for time serie

Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips

arXiv:2502.07408v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) can be catastrophically disrupted by flipping only a handful of parameter bits. We introduce Deep Neural Lesion (D

ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation

arXiv:2604.07021v2 Announce Type: replace Abstract: Weakly supervised semantic segmentation aims to achieve pixel-level predictions using image-level labels. Existing methods typically entangle semant

On the Expressive Power and Limitations of Multi-Layer SSMs

arXiv:2604.14501v1 Announce Type: new Abstract: We study the expressive power and limitations of multi-layer state-space models (SSMs). First, we show that multi-layer SSMs face fundamental limitation

Open-Set Vein Biometric Recognition with Deep Metric Learning

arXiv:2604.14874v1 Announce Type: new Abstract: Most state-of-the-art vein recognition methods rely on closed-set classification, which inherently limits their scalability and prevents the adaptive en

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation

arXiv:2603.13683v2 Announce Type: replace Abstract: Although debiased large language models (LLMs) excel at handling known or low-bias prompts, they often fail on unfamiliar and high-bias prompts. We

safetyarxiv-cs-cl

Query pipeline optimization for cancer patient question answering systems

arXiv:2412.14751v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) mitigates hallucination in Large Language Models (LLMs) by using query pipelines to retrieve relevant external

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base

Reward-Aware Trajectory Shaping for Few-step Visual Generation

arXiv:2604.14910v1 Announce Type: new Abstract: Achieving high-fidelity generation in extremely few sampling steps has long been a central goal of generative modeling. Existing approaches largely rely

SafeHarness: Lifecycle-Integrated Security Architecture for LLM-based Agent Deployment

model-releasesarxiv-cs-ai

arXiv:2604.13630v1 Announce Type: cross Abstract: The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use, context

Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local …

model-releasesclem-delangue--x

Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local agents are today: # Start llama.cpp server: llama-server -hf

Industry

Tesla is officially launching in Estonia. The company is holding an opening event on April 24th at Ülemiste Center 'Bring your friends and f…

Tesla is officially launching in Estonia. The company is holding an opening event on April 24th at Ülemiste Center 'Bring your friends and family to see our models, take part in the day’s activities a

industryelon-musk--x

Applications

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener

applicationsarxiv-cs-cl

Theory of Mind in Action: The Instruction Inference Task in Dynamic Human-Agent Collaboration

arXiv:2507.02935v2 Announce Type: replace Abstract: Successful human-agent teaming relies on an agent being able to understand instructions given by a (human) principal. In many cases, an instruction

Agents

Towards AI-assisted Neutrino Flavor Theory Design

arXiv:2506.08080v2 Announce Type: replace-cross Abstract: Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A

agentsarxiv-cs-lg

Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion

arXiv:2511.14178v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential in real-world robotic manipulation. However, pre-trained VLA policies st

safetyarxiv-cs-ro

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity

arXiv:2507.23121v2 Announce Type: replace Abstract: In this work, we study a critical research problem regarding the trustworthiness of large language models (LLMs): how LLMs behave when encountering

VeriGraphi: A Multi-Agent Framework of Hierarchical RTL Generation for Large Hardware Designs

model-releasesarxiv-cs-lg

arXiv:2604.14550v1 Announce Type: cross Abstract: Generating synthesizable Verilog for large, hierarchical hardware designs remains a significant challenge for large language models (LLMs), which stru

When Fairness Metrics Disagree: Evaluating the Reliability of Demographic Fairness Assessment in Machine Learning

arXiv:2604.15038v1 Announce Type: cross Abstract: The evaluation of fairness in machine learning systems has become a central concern in high-stakes applications, including biometric recognition, heal

When PCOS Meets Eating Disorders: An Explainable AI Approach to Detecting the Hidden Triple Burden

arXiv:2604.14356v1 Announce Type: new Abstract: Women with polycystic ovary syndrome (PCOS) face substantially elevated risks of body image distress, disordered eating, and metabolic challenges, yet e

Agents

yeah, what they said 🤝 a decent harness gets you an actually functioning agent now + teams that actually invest time in their harness+probl…

yeah, what they said 🤝 a decent harness gets you an actually functioning agent now + teams that actually invest time in their harness+problem design, choosing good infra, self-improvement loops, data

agentsharrison-chase--x

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction

model-releasesarxiv-cs-lg

arXiv:2604.13369v1 Announce Type: cross Abstract: Surrogate modeling of body-driven fluid flows where immersed moving boundaries couple structural dynamics to chaotic, unsteady fluid phenomena remains

AI Powered Image Analysis for Phishing Detection

arXiv:2604.13555v1 Announce Type: new Abstract: Phishing websites now rely heavily on visual imitation-copied logos, similar layouts, and matching colours-to avoid detection by text- and URL-based sys

Analog Optical Inference on Million-Record Mortgage Data

model-releasesarxiv-cs-lg

arXiv:2604.13251v1 Announce Type: new Abstract: Analog optical computers promise large efficiency gains for machine learning inference, yet no demonstration has moved beyond small-scale image benchmar

AudioX: A Unified Framework for Anything-to-Audio Generation

arXiv:2503.10522v4 Announce Type: replace-cross Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a

CLIP Architecture for Abdominal CT Image-Text Alignment and Zero-Shot Learning: Investigating Batch Composition and Data Scaling

arXiv:2604.13561v1 Announce Type: new Abstract: Vision-language models trained with contrastive learning on paired medical images and reports show strong zero-shot diagnostic capabilities, yet the eff

Coherence in the brain unfolds across separable temporal regimes

arXiv:2512.20481v4 Announce Type: replace-cross Abstract: To maintain coherence in language, the brain must satisfy key competing temporal demands: the gradual accumulation of meaning across extended

Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding

arXiv:2604.13313v1 Announce Type: new Abstract: Vision-Language Models demonstrate remarkable capabilities but often struggle with compositional reasoning, exhibiting vulnerabilities regarding word or

Context Sensitivity Improves Human-Machine Visual Alignment

arXiv:2604.13883v1 Announce Type: new Abstract: Modern machine learning models typically represent inputs as fixed points in a high-dimensional embedding space. While this approach has been proven pow

Correct Chains, Wrong Answers: Dissociating Reasoning from Output in LLM Logic

arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench

DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs

arXiv:2604.13075v1 Announce Type: new Abstract: Effective de-escalation is critical for law enforcement safety and community trust, yet traditional training methods lack scalability and realism. While

DiffMagicFace: Identity Consistent Facial Editing of Real Videos

arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid

researcharxiv-cs-cv