Search: “models”

Context-Aware Hospitalization Forecasting Evaluations for Decision Support using LLMs

arXiv:2604.23949v1 Announce Type: new Abstract: Medical and public health experts must make real-time resource decisions, such as expanding hospital bed capacity, based on projected hospitalization tr

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

DGX agent

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

model-releasesarxiv-cs-ai

28 Apr 2026

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

GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems

arXiv:2604.24477v1 Announce Type: cross Abstract: The rapid integration of Large Language Models (LLMs) into Multi-Agent Systems (MAS) has significantly enhanced their collaborative problem-solving ca

Guided Speculative Inference for Efficient Test-Time Alignment of LLMs

arXiv:2506.04118v3 Announce Type: replace Abstract: We propose Guided Speculative Inference (GSI), a novel algorithm for efficient reward-guided decoding in large language models. GSI combines soft be

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I'm so confused…

model-releasesjeremy-howard--x

I'm so confused… We're excited to partner with Google to offer Grounding With Exa inside of Gemini models! Using Exa's agent-first search, Gemini models can now access billions of websites, technical

Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents

model-releaseshugging-face

NVIDIA's Nemotron 3 Nano Omni is a lightweight multimodal AI model capable of processing documents, audio, and video inputs for building intelligent agents. The model supports long-context understandi

Knowledge Vector of Logical Reasoning in Large Language Models

arXiv:2604.23877v1 Announce Type: new Abstract: Logical reasoning serve as a central capability in LLMs and includes three main forms: deductive, inductive, and abductive reasoning. In this work, we s

researcharxiv-cs-cl

LILogic Net: Compact Logic Gate Networks with Learnable Connectivity for Efficient Hardware Deployment

arXiv:2511.12340v2 Announce Type: replace Abstract: Efficient machine learning deployment requires models that account for hardware constraints. Because binary logic gates are the fundamental primitiv

researcharxiv-cs-lg

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling

model-releasesarxiv-cs-cl

arXiv:2604.24715v1 Announce Type: new Abstract: Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transforme

MermaidSeqBench: An Evaluation Benchmark for NL-to-Mermaid Sequence Diagram Generation

arXiv:2511.14967v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown great promise in generating structured diagrams from natural language descriptions, particularly Merma

Meta-CoT: Enhancing Granularity and Generalization in Image Editing

arXiv:2604.24625v1 Announce Type: cross Abstract: Unified multi-modal understanding/generative models have shown improved image editing performance by incorporating fine-grained understanding into the

ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services

arXiv:2604.24023v1 Announce Type: new Abstract: Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their p

Sphere-Depth: A Benchmark for Depth Estimation Methods with Varying Spherical Camera Orientations

arXiv:2604.23432v1 Announce Type: cross Abstract: Reliable depth estimation from spherical images is crucial for 360{eg} vision in robotic navigation and immersive scene understanding. However, the on

The Pragmatic Persona: Discovering LLM Persona through Bridging Inference

arXiv:2604.24079v1 Announce Type: cross Abstract: Large Language Models (LLMs) reveal inherent and distinctive personas through dialogue. However, most existing persona discovery approaches rely on su

Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging

arXiv:2505.16024v2 Announce Type: replace-cross Abstract: Diffusion trajectory distillation accelerates sampling by training a student model to approximate the multi-step denoising trajectories of a p

researcharxiv-cs-ai

UpstreamQA: A Modular Framework for Explicit Reasoning on Video Question Answering Tasks

arXiv:2604.23145v1 Announce Type: cross Abstract: Video Question Answering (VideoQA) demands models that jointly reason over spatial, temporal, and linguistic cues. However, the task's inherent comple

YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review

arXiv:2501.13400v3 Announce Type: replace-cross Abstract: In the field of deep learning-based computer vision, YOLO is revolutionary. With respect to deep learning models, YOLO is also the one that is

researcharxiv-cs-ai

Zero-to-CAD: Agentic Synthesis of Interpretable CAD Programs at Million-Scale Without Real Data

arXiv:2604.24479v1 Announce Type: new Abstract: Computer-Aided Design (CAD) models are defined by their construction history: a parametric recipe that encodes design intent. However, existing large-sc

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution

arXiv:2604.22192v1 Announce Type: new Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are

CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language

arXiv:2604.22367v1 Announce Type: cross Abstract: Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs t

Conditional Diffusion Posterior Alignment for Sparse-View CT Reconstruction

arXiv:2604.21960v1 Announce Type: cross Abstract: Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, t

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Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework

arXiv:2604.22119v1 Announce Type: new Abstract: As reasoning capacity and deployment scope grow in tandem, large language models (LLMs) gain the capacity to engage in behaviors that serve their own ob

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Applications

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

Applications

Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation

arXiv:2604.22098v1 Announce Type: new Abstract: Time introduces fundamental challenges in model development and deployment: models are usually trained on historical data while deployed on future data

applicationsarxiv-cs-cl

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation

arXiv:2604.22302v1 Announce Type: new Abstract: Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reliab

Learning from Natural Language Feedback for Personalized Question Answering

arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se

Recognition Without Authorization: LLMs and the Moral Order of Online Advice

arXiv:2604.22143v1 Announce Type: cross Abstract: Large language models are increasingly used to mediate everyday interpersonal dilemmas, yet how their advisory defaults interact with the concentrated

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Tensor Network Estimation of Distribution Algorithms

arXiv:2412.19780v2 Announce Type: replace Abstract: Tensor networks are a tool first employed in the context of many-body quantum physics that now have a wide range of uses across the computational sc

researcharxiv-cs-lg

Thermal background reduction for mid-infrared imaging by low-rank background and sparse point-source modelling

arXiv:2604.22351v1 Announce Type: cross Abstract: Mid-infrared astronomy from the ground faces critical challenges in accurately detecting and quantifying sources due to the dominant spatially and tim

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TreeCoder: Systematic Exploration and Optimisation of Decoding and Constraints for LLM Code Generation

model-releasesarxiv-cs-lg

arXiv:2511.22277v2 Announce Type: replace Abstract: Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when

TuneForge: an MCP server that lets your coding agent (Claude, Cursor, etc.) handle dataset generation, LoRA fine-tuning, RL, and evaluation directly in chat

TuneForge is an MCP (Model Context Protocol) server that enables coding agents like Claude and Cursor to perform machine learning operations directly within chat interfaces, including dataset generati

model-releasesr-ollama

Xiaomi MiMo-V2.5 is now officially open-sourced！ MIT License, supporting commercial deployment, continued training, and fine-tuning - no add…

model-releasesjeremy-howard--x

Xiaomi MiMo-V2.5 is now officially open-sourced！ MIT License, supporting commercial deployment, continued training, and fine-tuning - no additional authorization required. Two models, both supporting

April was a pretty strong month for LLM releases: - Gemma 4 - GLM-5.1 - Qwen3.6 - Kimi K2.6 - DeepSeek V4 All are now added to the LLM Archi…

model-releasessebastian-raschka--x

April saw significant activity in large language model releases, with five major models introduced including Gemma 4, GLM-5.1, Qwen 3.6, Kimi K2.6, and DeepSeek V4. These releases have been added to a

26 Apr 2026

pay attention anon. this is what local ai actually feels like in 2026. qwen 3.6 27b dense just knocked down the second test in my single fil…

model-releasesclem-delangue--x

pay attention anon. this is what local ai actually feels like in 2026. qwen 3.6 27b dense just knocked down the second test in my single file agentic benchmark series. on 1x 3090. mandelbrot fractal e

26 Apr 2026

🤗 DeepSeek V4 is now live on @huggingface — supported by Novita 1M context. Massive-scale MoE. Pro or Flash — pick your tradeoff.

model-releasesclem-delangue--x

DeepSeek V4, a large-scale mixture-of-experts (MoE) model, is now available on Hugging Face with support from Novita offering 1 million token context window. The model is offered in two variants—Pro a

25 Apr 2026

CAP: Controllable Alignment Prompting for Unlearning in LLMs

arXiv:2604.21251v1 Announce Type: cross Abstract: Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearni

Congrats to @deepseek_ai team! Doing the numbers I would estimate: Pro < 14m for the final training run Flash < 4m Ratio of active params …

model-releasesemad-mostaque--x

Congrats to @deepseek_ai team! Doing the numbers I would estimate: Pro < 14m for the final training run Flash < 4m Ratio of active params x total training tokens vs v3 Total compute costs (data prep,

CSC: Turning the Adversary's Poison against Itself

arXiv:2604.21416v1 Announce Type: cross Abstract: Poisoning-based backdoor attacks pose significant threats to deep neural networks by embedding triggers in training data, causing models to misclassif

DEEPSEEK-V4 IS RELEASED

model-releasesclem-delangue--x

DeepSeek-V4 is a newly released AI model announced by Clem Delangue on X (formerly Twitter). The release likely represents an updated version of the DeepSeek model series with improvements in capabili

DMAP: A Distribution Map for Text

arXiv:2602.11871v2 Announce Type: replace Abstract: Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offer

researcharxiv-cs-cl

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming

model-releasesarxiv-cs-lg

arXiv:2505.05261v3 Announce Type: replace-cross Abstract: Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a cha

Neural surrogates for crystal growth dynamics with variable supersaturation: explicit vs. implicit conditioning

model-releasesarxiv-cs-lg

arXiv:2604.21753v1 Announce Type: cross Abstract: Simulations of crystal growth are performed by using Convolutional Recurrent Neural Network surrogate models, trained on a dataset of time sequences c

Local Ai

Neutron and X-ray Diffraction Reveal the Limits of Long-Range Machine Learning Potentials for Medium-Range Order in Silica Glass

arXiv:2604.21222v1 Announce Type: cross Abstract: Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge f

local-aiarxiv-cs-lg

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

arXiv:2510.13918v2 Announce Type: replace Abstract: Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language mode

researcharxiv-cs-cl

OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving

model-releasesarxiv-cs-cl

arXiv:2604.21510v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning, complex optimization tasks remain challenging, requiring domain knowledge and robus

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs

arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-

researcharxiv-cs-ai

Robustness Analysis of POMDP Policies to Observation Perturbations

arXiv:2604.21256v1 Announce Type: new Abstract: Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviat

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