Search: “routing”

Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning

model-releasesarxiv-cs-ai

arXiv:2605.18871v1 Announce Type: cross Abstract: When Large Language Models produce structured outputs such as travel plans, code solutions, or multi-step proofs, individual reasoning steps may appea

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Model Releases

DynaTrain: Fast Online Parallelism Switching for Elastic LLM Training

DGX agent

arXiv:2605.18815v1 Announce Type: new Abstract: Modern large language model (LLM) training is inherently dynamic: resource fluctuations, RLHF phase shifts, and cluster elasticity continually reshape t

model-releasesarxiv-cs-lg

20 May 2026

EgoTraj: Real-World Egocentric Human Trajectory Dataset for Multimodal Prediction

model-releasesarxiv-cs-cv

arXiv:2605.19004v1 Announce Type: new Abstract: Accurately forecasting human trajectories from an egocentric perspective plays a central role in applications such as humanoid robotics, wearable sensin

Exact Linear Attention

arXiv:2605.18848v1 Announce Type: cross Abstract: This paper introduces Exact Linear Attention (ELA), a mechanism that achieves linear computational complexity for Transformer attention by leveraging

Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents

arXiv:2605.19604v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly act inside real workspaces, where tools and skills determine whether model reasoning becomes reliable act

fun read on real tradeoffs & design decisions we debated when designing Engine for the data scale that customers produce one common thread i…

model-releasesharrison-chase--x

fun read on real tradeoffs & design decisions we debated when designing Engine for the data scale that customers produce one common thread is that we’re pretty strong supporters of just giving the age

Hardware

GEM: GPU-Variability-Aware Expert to GPU Mapping for MoE Systems

arXiv:2605.19945v1 Announce Type: cross Abstract: Mixture-of-Expert (MoE) models enable efficient inference by employing smaller experts and activating only a subset of them per token. MoE serving eng

hardwarearxiv-cs-ai

Generative-Evaluative Agreement: A Necessary Validity Criterion for LLM-Enabled Adaptive Assessment

arXiv:2605.19529v1 Announce Type: new Abstract: When the same LLM generates assessment items, simulates student responses, and scores them, the validation loop is self-referential. We introduce Genera

Google I/O, Gemini Spark, Antigravity

model-releasessimon-willison

It's hard to find much to write about Google I/O this year because I have a policy of not writing about anything that I can't try out myself, and a lot of the big announcements are 'coming soon'. I ac

HELLoRA: Hot Experts Layer-Level Low-Rank Adaptation for Mixture-of-Experts Models

model-releasesarxiv-cs-ai

arXiv:2605.18795v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) dominates parameter-efficient fine-tuning of large language models, yet most variants target dense architectures. Mixture-o

iGSP:Implicit Gradient Subspace Projection for Efficient Continual Learning of Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.19301v1 Announce Type: new Abstract: Vision-Language Models require efficient adaptation to continually emerging downstream tasks. While Parameter-Efficient Fine-Tuning mitigates catastroph

Local Ai

Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

arXiv:2605.19140v1 Announce Type: new Abstract: We study workflow learning in a setting where specialized agents hand off control through a shared artifact, each agent observes only a local function o

local-aiarxiv-cs-ai

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators

arXiv:2605.19060v1 Announce Type: cross Abstract: High-resolution 3D medical image generation remains challenging because fully volumetric models are computationally expensive, while efficient 2D slic

Agents

MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent

arXiv:2605.19194v1 Announce Type: new Abstract: The Mixture-of-Agents (MoA) framework has shown promise in improving large language model (LLM) performance by aggregating outputs from multiple agents.

agentsarxiv-cs-cl

Agents

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization

arXiv:2605.19330v1 Announce Type: new Abstract: LLM agents organize behavior through skills - structured natural-language specifications governing how an agent reasons, retrieves, and responds. Unlike

agentsarxiv-cs-ai

Not All Tokens Are Worth Caching: Learning Semantic-Aware Eviction for LLM Prefix Caches

model-releasesarxiv-cs-lg

arXiv:2605.18825v1 Announce Type: new Abstract: Prefix caching is a key optimization in Large Language Model (LLM) serving, reusing attention Key-Value (KV) states across requests with shared prompt p

Applications

Performance Monitoring of Proton Exchange Membrane Water Electrolyzer by Transformers-Based Machine Learning Model

arXiv:2605.19107v1 Announce Type: new Abstract: Green hydrogen plays an essential role in decarbonization, with capacity projected to scale to 560 GW by 2030 (vs. 1.39 GW in 2023) in net-zero settings

applicationsarxiv-cs-lg

Phase-Aware Mixture of Experts for Agentic Reinforcement Learning

arXiv:2602.17038v3 Announce Type: replace Abstract: Reinforcement learning (RL) has equipped LLM agents with a strong ability to solve complex tasks. However, existing RL methods normally use a single

Hardware

PiKV: KV Cache Management System for Mixture of Experts

arXiv:2508.06526v3 Announce Type: replace-cross Abstract: As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache

hardwarearxiv-cs-ai

Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming

arXiv:2605.19052v1 Announce Type: cross Abstract: Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposab

researcharxiv-cs-lg

SceneCode: Executable World Programs for Editable Indoor Scenes with Articulated Objects

arXiv:2605.19587v1 Announce Type: new Abstract: Indoor scene synthesis underpins embodied AI, robotic manipulation, and simulation-based policy evaluation, where a useful scene must specify not only w

Tight Regret Bounds for Fixed-Price Bilateral Trade

arXiv:2504.04349v3 Announce Type: replace-cross Abstract: We examine fixed-price mechanisms in bilateral trade through the lens of regret minimization. Our main results are twofold. (i) For independen

researcharxiv-cs-lg

Unified Deployment-Aware Evaluation of Open Reasoning Language Models

model-releasesarxiv-cs-cl

arXiv:2604.07035v2 Announce Type: replace Abstract: Open reasoning language models are often compared under mixed sample sizes, partially standardized prompts, and accuracy-centered summaries, which m

What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code

arXiv:2605.19762v1 Announce Type: new Abstract: Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the

A Unified Framework for Data-Free One-Step Sampling via Wasserstein Gradient Flows

arXiv:2605.17808v1 Announce Type: new Abstract: We develop a unified theoretical framework for data-free one-step sampling from unnormalized target distributions based on Wasserstein gradient flows. F

researcharxiv-cs-lg

Beyond Linear Superposition: Discovering Climate Features in AI Weather Models with KAN-SAE

arXiv:2605.17493v1 Announce Type: cross Abstract: Deep learning weather prediction models achieve remarkable predictive skill yet remain largely opaque: we know little about how they represent physica

Body-Grounded Perspective Formation and Conative Attunement in Artificial Agents

arXiv:2605.16728v1 Announce Type: new Abstract: This paper proposes a minimal architecture for body-grounded perspective formation in artificial agents. Extending prior work, the model introduces an i

Capturing LLM Capabilities via Evidence-Calibrated Query Clustering

arXiv:2605.17110v1 Announce Type: new Abstract: Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing cluster

Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction

arXiv:2605.16832v1 Announce Type: new Abstract: Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud en

researcharxiv-cs-cv

Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning

arXiv:2605.16824v1 Announce Type: cross Abstract: Large language models (LLMs) generate not only reasoning text, but also token-level confidence trajectories that record how uncertainty evolves during

researcharxiv-cs-cl

Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting

model-releasesarxiv-cs-cv

arXiv:2508.04227v2 Announce Type: replace Abstract: Vision-language models (VLMs) and the recent surge of Multimodal Large Language Models (MLLMs) have revolutionized artificial intelligence with unpr

Agents

DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition

arXiv:2605.16441v1 Announce Type: cross Abstract: Beat-level Electrocardiography (ECG) arrhythmia detection aims to assign an arrhythmia class to each beat in a recording, yet many existing systems tr

agentsarxiv-cs-ai

Distilling Tabular Foundation Models for Structured Health Data

arXiv:2605.18702v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) achieve strong performance on health datasets, but their inference cost and infrastructure requirements limit practic

Domain Transfer Becomes Identifiable via a Single Alignment

arXiv:2605.17918v1 Announce Type: cross Abstract: Domain transfer (DT) maps source to target distributions and supports tasks such as unsupervised image-to-image translation, single-cell analysis, and

Tutorials

Encoding Robust Topological Signatures for Hyperdimensional Computing

arXiv:2605.16785v1 Announce Type: cross Abstract: Hyperdimensional (HD) computing offers an attractive alternative to deep networks for edge learning due to its simplicity, fast prototype-based infere

tutorialsarxiv-cs-ai

EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers

arXiv:2605.16745v1 Announce Type: new Abstract: This paper addresses the challenge of integrating 3D meshes as a native modality within Multimodal Large Language Models (MLLMs). Diffusion-based large

researcharxiv-cs-cv

Everything Google Cloud customers need to know coming out of Google I/O

model-releasesgoogle-cloud-ai

At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace I

Experimentally validated quantum-secure federated learning over a multi-user quantum network

model-releasesarxiv-cs-ai

arXiv:2501.12709v2 Announce Type: replace-cross Abstract: Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum fe

GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

model-releasesarxiv-cs-ro

arXiv:2506.14009v2 Announce Type: replace Abstract: Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Y

How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning

arXiv:2605.16591v1 Announce Type: cross Abstract: In-context learning (ICL) excels at new tasks from minimal examples, yet we still lack a mechanistic explanation of how few-shot prompts shape a model

Local Ai

I made a tool to use AgentRouter models in OpenCode

The search results focus on OpenCode + Ollama integration but don't specifically cover the AgentRouter tool. Let me provide a knowledge base entry based on what the title and context suggest: A tool d

local-air-ollama

Latent Heuristic Search: Continuous Optimization for Automated Algorithm Design

arXiv:2605.17137v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into evolutionary frameworks has established a new paradigm for automated heuristic discovery. Despite t

Learned Memory Attenuation in Sage-Husa Kalman Filters for Robust UAV State Estimation

model-releasesarxiv-cs-lg

arXiv:2605.18704v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles in dynamic environments face telemetry outages, structural vibrations, and regime-dependent noise that invalidate the station

Learning Unbiased Permutations via Flow Matching

arXiv:2605.16755v1 Announce Type: cross Abstract: Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn prod

Tutorials

Leveraging Latent Visual Reasoning in Silence

arXiv:2605.18641v1 Announce Type: new Abstract: Latent visual reasoning involves visual evidence more directly in multimodal reasoning by inserting continuous latent tokens before textual generation.

tutorialsarxiv-cs-cv

Tutorials

LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging

arXiv:2605.16264v1 Announce Type: cross Abstract: Push notifications remain among the most direct channels through which digital platforms engage users, yet existing approaches have invested heavily i

tutorialsarxiv-cs-cl

Memory-Guided Tree Search with Cross-Branch Knowledge Transfer for LLM Solver Synthesis

arXiv:2605.17539v1 Announce Type: new Abstract: Combinatorial optimization (CO) underlies decision-making from logistics to chip design, where infeasible solutions are operationally unusable and small

Applications

One trend that I think you might start to see at big companies is insourcing via hiring: why pay so many outside vendors (legal, marketing, …

applicationsethan-mollick--x

One trend that I think you might start to see at big companies is insourcing via hiring: why pay so many outside vendors (legal, marketing, software vendors) when you can hire in-house and harness AI