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KaLDeX: Kalman Filter based Linear Deformable Cross Attention for Retina Vessel Segmentation

arXiv:2410.21160v2 Announce Type: replace-cross Abstract: Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various

researcharxiv-cs-cv

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Karpathy's autoresearch repo started an impressive trend. Agents can now train AI models to build SoTA agentic systems. And to think this is…

DGX agent

Karpathy's autoresearch repo started an impressive trend. Agents can now train AI models to build SoTA agentic systems. And to think this is just scratching the surface. Ultimately, it boils down to g

hardwareclem-delangue--x

21 Apr 2026

Keep improving 🚀🚀 @arena

Keep improving 🚀🚀 @arena Qwen3.6 Plus lands at #7 in Code Arena with a score of 1476 - up +16 points since the Preview. The new score also moves @AlibabaGroup to #3 lab in Code Arena. In the Text Aren

model-releasesqwen--x

Kevin Warsh just lost me. He argues he's going to be an independent Fed Chair, but refuses to acknowledge that Trump lost the 2020 election.…

Kevin Warsh just lost me. He argues he's going to be an independent Fed Chair, but refuses to acknowledge that Trump lost the 2020 election. If you can't state simple facts when you're in the politica

researchyann-lecun--x

Kimi 2.6 Thinking seems very good for an open weights model, but many rough edges compared to closed SoTA. The Lem Test resulted in a 74 pag…

applicationsethan-mollick--x

Kimi 2.6 Thinking seems very good for an open weights model, but many rough edges compared to closed SoTA. The Lem Test resulted in a 74 page thinking trace... and an okay-ish answer. It did an okay T

Kimi is the current open-source SOTA on Artificial Analysis

Kimi is the current open-source SOTA on Artificial Analysis Moonshot’s Kimi K2.6 is the new leading open weights model. Kimi K2.6 lands at #4 on the Artificial Analysis Intelligence Index (54) behind

agentskimi-moonshot--x

📢 Kimi K2.6 API is live • Input Price (Cache Hit): 0.16 / M tokens • Input Price (Cache Miss): 0.95 / M tokens • Output: $4.00 / M tokens…

📢 Kimi K2.6 API is live • Input Price (Cache Hit): 0.16 / M tokens • Input Price (Cache Miss): 0.95 / M tokens • Output: $4.00 / M tokens Kimi K2.6 is our latest + most intelligent model - stronger lo

Kimi K2.6 autonomously overhauled exchange-core, an 8-year-old open-source financial matching engine. Over a 13-hour execution, the model it…

Kimi K2.6 autonomously overhauled exchange-core, an 8-year-old open-source financial matching engine. Over a 13-hour execution, the model iterated through 12 optimization strategies, initiating over 1

Local Ai

Kimi K2.6 demonstrates strong long-horizon coding in complex engineering tasks: Kimi K2.6 successfully downloaded and deployed the Qwen3.5-0…

Kimi K2.6 demonstrates strong long-horizon coding in complex engineering tasks: Kimi K2.6 successfully downloaded and deployed the Qwen3.5-0.8B model locally on a Mac. By implementing and optimizing m

local-aikimi-moonshot--x

Kimi K2.6 has captured #1 on the open-weight Vals Index, and is #7 overall.

Kimi K2.6, a language model developed by Moonshot AI, has achieved the top ranking on the open-weight category of the Vals Index benchmark, while placing 7th overall across all model categories. The V

Kimi K2.6 is now available in Windsurf! Available for free for the next 2 weeks for Pro, Teams, and Max users.

Cognition AI has made Kimi K2.6, an advanced language model, available within their Windsurf IDE for free during a two-week promotional period. This access is offered to Pro, Teams, and Max subscripti

agentscognition-ai--x

Kimi K2.6 is now live inside Anything!

Kimi K2.6, an AI model from Moonshot, has been integrated into the Anything platform. This update likely enables users to access Kimi's capabilities directly within the Anything application interface.

Kimi K2.6 @Kimi_Moonshot is the new leading open-weights agent model, landing at #4 on Claw-Eval (Pass^3: 62.3%). Key takeaways: - 👑 Best o…

Kimi K2.6 @Kimi_Moonshot is the new leading open-weights agent model, landing at #4 on Claw-Eval (Pass^3: 62.3%). Key takeaways: - 👑 Best open-source agent, period: Pass^3 of 62.3% is the highest of a

Local Ai

Kimi Kimi 。 Kimi Kimi Kimi Kimi Kimi Kimi ollama run kimi-k2.6:cloud

This appears to be a social media post from Ollama's X account regarding a model run command for 'kimi-k2.6:cloud,' likely announcing or demonstrating how to execute this specific AI model variant usi

local-aiollama--x

KIRA: Knowledge-Intensive Image Retrieval and Reasoning Architecture for Specialized Visual Domains

model-releasesarxiv-cs-cv

arXiv:2604.16915v1 Announce Type: new Abstract: Retrieval augmented generation (RAG) has transformed text based question answering, yet its extension to visual domains remains hindered by fundamental

Knowing When to Quit: A Principled Framework for Dynamic Abstention in LLM Reasoning

arXiv:2604.18419v1 Announce Type: cross Abstract: Large language models (LLMs) using chain-of-thought reasoning often waste substantial compute by producing long, incorrect responses. Abstention can m

Knowledge without Wisdom: Measuring Misalignment between LLMs and Intended Impact

model-releasesarxiv-cs-lg

arXiv:2603.00883v2 Announce Type: replace Abstract: LLMs increasingly excel on AI benchmarks, but doing so does not guarantee validity for downstream tasks. This study contrasts LLM alignment on bench

L1 Regularization Paths in Linear Models by Parametric Gaussian Message Passing

arXiv:2604.16949v1 Announce Type: new Abstract: The paper considers the computation of L1 regularization paths in a state space setting, which includes L1 regularized Kalman smoothing, linear SVM, LAS

LAGS: Low-Altitude Gaussian Splatting with Groupwise Heterogeneous Graph Learning

arXiv:2604.16910v1 Announce Type: new Abstract: Low-altitude Gaussian splatting (LAGS) facilitates 3D scene reconstruction by aggregating aerial images from distributed drones. However, as LAGS priori

applicationsarxiv-cs-cv

🏆LangChain was just named 2026 @googlecloud Partner of the Year Award in the Marketplace: Agent Platform category. ☁️ @gcloudpartners #Goog…

LangChain received Google Cloud's 2026 Partner of the Year Award in the Marketplace: Agent Platform category, recognizing its contributions to the cloud ecosystem. The award highlights LangChain's pro

agentsharrison-chase--x

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users

arXiv:2603.16120v2 Announce Type: replace Abstract: Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queri

Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions

arXiv:2601.05414v2 Announce Type: replace Abstract: As large language models (LLMs) transition from chat interfaces to integral components of stochastic pipelines and systems approaching general intel

applicationsarxiv-cs-cl

Large Language Models Are Still Misled by Simple Bias Ensembles

arXiv:2505.16522v3 Announce Type: replace Abstract: With the evolution of large language models (LLMs), their robustness against individual simple biases has been enhanced. However, we observe that th

LASER: Low-Rank Activation SVD for Efficient Recursion

arXiv:2604.17224v1 Announce Type: new Abstract: Recursive architectures such as Tiny Recursive Models (TRMs) perform implicit reasoning through iterative latent computation, yet the geometric structur

Safety

Last Wednesday, our founder and scientific advisor, @Yoshua_Bengio, was officially appointed an Officer of the Order of the British Empire (…

Last Wednesday, our founder and scientific advisor, @Yoshua_Bengio, was officially appointed an Officer of the Order of the British Empire (OBE). This prestigious distinction recognizes his contributi

safetyyoshua-bengio--x

Late Fusion Neural Operators for Extrapolation Across Parameter Space in Partial Differential Equations

model-releasesarxiv-cs-lg

arXiv:2604.16721v1 Announce Type: new Abstract: Developing neural operators that accurately predict the behavior of systems governed by partial differential equations (PDEs) across unseen parameter re

Latent Abstraction for Retrieval-Augmented Generation

arXiv:2604.17866v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a standard approach for enhancing large language models (LLMs) with external knowledge, mitigating hallu

researcharxiv-cs-cl

Latent-Compressed Variational Autoencoder for Video Diffusion Models

arXiv:2604.16479v1 Announce Type: new Abstract: Video variational autoencoders (VAEs) used in latent diffusion models typically require a sufficiently large number of latent channels to ensure high-qu

researcharxiv-cs-cv

Latent Phase-Shift Rollback: Inference-Time Error Correction via Residual Stream Monitoring and KV-Cache Steering

arXiv:2604.18567v1 Announce Type: cross Abstract: Large language models frequently commit unrecoverable reasoning errors mid-generation: once a wrong step is taken, subsequent tokens compound the mist

researcharxiv-cs-cl

Latent Preference Modeling for Cross-Session Personalized Tool Calling

arXiv:2604.17886v1 Announce Type: new Abstract: Users often omit essential details in their requests to LLM-based agents, resulting in under-specified inputs for tool use. This poses a fundamental cha

Safety

LatentMimic: Terrain-Adaptive Locomotion via Latent Space Imitation

arXiv:2604.16440v1 Announce Type: new Abstract: Developing natural and diverse locomotion controllers for quadruped robots that can adapt to complex terrains while preserving motion style remains a si

safetyarxiv-cs-ro

LayerCache: Exploiting Layer-wise Velocity Heterogeneity for Efficient Flow Matching Inference

model-releasesarxiv-cs-cv

arXiv:2604.16492v1 Announce Type: new Abstract: Flow Matching models achieve state-of-the-art image generation quality but incur substantial inference cost due to iterative denoising through large Tra

LBFTI: Layer-Based Facial Template Inversion for Identity-Preserving Fine-Grained Face Reconstruction

arXiv:2604.18358v1 Announce Type: new Abstract: In face recognition systems, facial templates are widely adopted for identity authentication due to their compliance with the data minimization principl

researcharxiv-cs-cv

LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations

arXiv:2509.12539v2 Announce Type: replace-cross Abstract: We present LEAF ('Lightweight Embedding Alignment Framework'), a knowledge distillation framework for text embedding models. A key distinguish

Learned Nonlocal Feature Matching and Filtering for RAW Image Denoising

model-releasesarxiv-cs-cv

arXiv:2604.17453v1 Announce Type: cross Abstract: Being one of the oldest and most basic problems in image processing, image denoising has seen a resurgence spurred by rapid advances in deep learning.

Safety

Learning-Based Sparsification of Dynamic Graphs in Robotic Exploration Algorithms

arXiv:2604.16509v1 Announce Type: cross Abstract: Many robotic exploration algorithms rely on graph structures for frontier-based exploration and dynamic path planning. However, these graphs grow rapi

safetyarxiv-cs-lg

Learning from Less: Measuring the Effectiveness of RLVR in Low Data and Compute Regimes

arXiv:2604.18381v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) typically relies on large quantities of high-quality annotated data, or questions with well-defined ground tr

applicationsarxiv-cs-lg

Tutorials

Learning Invariant Modality Representation for Robust Multimodal Learning from a Causal Inference Perspective

arXiv:2604.18460v1 Announce Type: new Abstract: Multimodal affective computing aims to predict humans' sentiment, emotion, intention, and opinion using language, acoustic, and visual modalities. Howev

tutorialsarxiv-cs-lg

Learning residue level protein dynamics with multiscale Gaussians

arXiv:2509.01038v2 Announce Type: replace-cross Abstract: Many methods have been developed to predict static protein structures, however understanding the dynamics of protein structure is essential fo

Learning Stable Predictors from Weak Supervision under Distribution Shift

model-releasesarxiv-cs-lg

arXiv:2604.05002v2 Announce Type: replace Abstract: Learning from weak, proxy, or relative supervision is common when ground-truth labels are unavailable, but robustness under distribution shift remai

Learning the Riccati solution operator for time-varying LQR via Deep Operator Networks

arXiv:2604.18507v1 Announce Type: cross Abstract: We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadrati

Learning to Control Summaries with Score Ranking

arXiv:2604.17197v1 Announce Type: new Abstract: Recent advances in summarization research focus on improving summary quality across multiple criteria, such as completeness, conciseness, and faithfulne

Learning to Correct: Calibrated Reinforcement Learning for Multi-Attempt Chain-of-Thought

arXiv:2604.17912v1 Announce Type: new Abstract: State-of-the-art reasoning models utilize long chain-of-thought (CoT) to solve increasingly complex problems using more test-time computation. In this w

Learning to Retrieve User History and Generate User Profiles for Personalized Persuasiveness Prediction

arXiv:2601.05654v3 Announce Type: replace Abstract: Estimating the persuasiveness of messages is critical in various applications, from recommender systems to safety assessment of LLMs. While it is im

Local Ai

Learning to Seek Help: Dynamic Collaboration Between Small and Large Language Models

arXiv:2604.17827v1 Announce Type: new Abstract: Large language models (LLMs) offer strong capabilities but raise cost and privacy concerns, whereas small language models (SLMs) facilitate efficient an

local-aiarxiv-cs-cl

Learning to Trade Like an Expert: Cognitive Fine-Tuning for Stable Financial Reasoning in Language Models

arXiv:2604.16862v1 Announce Type: new Abstract: Recent deployments of large language models (LLMs) as autonomous trading agents raise questions about whether financial decision-making competence gener

agentsarxiv-cs-lg

Learning Unanimously Acceptable Lotteries via Queries

arXiv:2604.17505v1 Announce Type: cross Abstract: Many high-stakes AI deployments proceed only if every stakeholder deems the system acceptable relative to their own minimum standard. With randomizati

Tutorials

Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking

arXiv:2604.17335v1 Announce Type: new Abstract: Whole-body humanoid locomotion is challenging due to high-dimensional control, morphological instability, and the need for real-time adaptation to vario

tutorialsarxiv-cs-ro