Search: “routing”

Choosing Where and How to Moderate: End-to-End Trade-offs in Filter Placement and Response Rewriting

model-releasesarxiv-cs-cl

arXiv:2607.26200v1 Announce Type: new Abstract: Content-moderation classifiers are usually evaluated in isolation, but deployment requires choosing where to intervene and what follows a flag. We evalu

30 Jul 2026

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Applications

ContactFlow: A video action conditioning that transfers across embodiments

DGX agent

arXiv:2607.26579v1 Announce Type: cross Abstract: World models offer a promising route toward robot planning by enabling agents to imagine and verify the consequences of actions before execution. Howe

applicationsarxiv-cs-cv

30 Jul 2026

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

arXiv:2607.26467v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ri

researcharxiv-cs-lg

30 Jul 2026

Understanding Knowledge Transfer Mechanism in Heterogeneous MLLM Fusion: A Simple Linear Approach

arXiv:2607.26608v1 Announce Type: new Abstract: Training-free fusion of heterogeneous multimodal large language models (MLLMs) provides a direct route for cross-scale capability transfer, yet improvem

30 Jul 2026

Applications

A2TTA: Anchored-and-Agile Test-Time Adaptation for Evolving Traffic Sensor Networks

arXiv:2607.25875v1 Announce Type: cross Abstract: Traffic forecasting is important for efficient traffic management and route planning in smart cities. Existing traffic forecasting studies typically a

applicationsarxiv-cs-ai

Conformal Cascade: Distribution-Free Accuracy Guarantees for Multi-Tier LLM Inference

model-releasesarxiv-cs-lg

arXiv:2607.25018v1 Announce Type: new Abstract: Large language model (LLM) cascades reduce inference cost by routing easy queries to a small model and deferring hard queries to a larger one. Productio

Loss Invariance Determines What Concept Layers Encode: Volume Grounding in Echocardiography

arXiv:2607.25748v1 Announce Type: new Abstract: Objective: Concept bottleneck models route prediction through interpretable intermediate variables, and their validity is normally judged by how accurat

researcharxiv-cs-ai

UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams

model-releasesarxiv-cs-cl

arXiv:2607.26017v1 Announce Type: new Abstract: Memory is essential for LLM agents to accumulate task experience and reuse task-specific execution strategies. However, real-world deployment over bound

Untrusted Authors, Trusted Answers: A Calculus of Fidelity-Graded Translations

arXiv:2607.14137v2 Announce Type: cross Abstract: To answer a question about a program, move the program to where the question is decidable. Every such move is a translation, and every translation is

researcharxiv-cs-ai

BATON: A Multimodal Benchmark for Bidirectional Automation Transition Observation in Naturalistic Driving

arXiv:2604.07263v2 Announce Type: replace-cross Abstract: Existing driving automation (DA) systems on production vehicles rely on human drivers to decide when to engage DA while requiring them to rema

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs

arXiv:2607.22577v1 Announce Type: new Abstract: Scaling large language models (LLMs) has driven their success, yet dense Transformers couple capacity and computation: every parameter is activated for

DY-LUT: Depth-Aware YCbCr Lookup Tables for Real-Time Underwater Image Enhancement

arXiv:2607.22801v1 Announce Type: cross Abstract: Underwater image enhancement is challenged by spatially non-uniform, wavelength-dependent attenuation. Propagation distance and wavelength govern this

Sol-Attn: Accelerating Video Generation Inference via On-the-Fly Attention Sparsification

arXiv:2607.24027v1 Announce Type: new Abstract: Diffusion transformers are essential for high-fidelity video generation, but long token sequences make attention a dominant inference bottleneck. Traini

Tools

Kimi K3 rivals Anthropic and OpenAI’s top models at a fraction of the cost. 3 / 1M input tokens. 15 / 1M output. $0.30 / 1M cached You can…

Kimi K3 rivals Anthropic and OpenAI’s top models at a fraction of the cost. 3 / 1M input tokens. 15 / 1M output. $0.30 / 1M cached You can now route your hardest reasoning to an open model without pay

toolsfireworks-ai--x

MoE^2-LoRA: When MoE Models Meet MoE-style Low-Rank Adaptation

model-releasesarxiv-cs-cl

arXiv:2607.21978v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures have been widely adopted in large language models, yet parameter-efficient fine-tuning (PEFT) for MoE models rema

Nexus connects to the agentic harnesses your teams already use, whether that’s Claude Code, Codex, OpenCode, or your own custom tooling. It …

model-releasesfireworks-ai--x

Nexus connects to the agentic harnesses your teams already use, whether that’s Claude Code, Codex, OpenCode, or your own custom tooling. It gives you: → Intelligent routing, automatically matching eac

Local Ai

Ornith-397B running at Q4 on a single RTX PRO 6000 Blackwell 96GB - 2,354 tok/s prefill, ~20–24 tok/s decode

I've been building Krasis, an MoE-focused runtime for streaming big models through limited VRAM on NVIDIA consumer/workstation GPUs, and I think this is the most interesting result so far: Ornith-1.0-

local-air-localllama

Has anyone compared pre-training, SFT/LoRA and reinforcement post-training on Qwen3.6-27B?

model-releasesr-localllama

Qwen3.6-27B: SFT vs continued pre-training vs RL? I’m interested in adapting Qwen3.6-27B, but I’m increasingly unsure whether conventional SFT/LoRA is the best route if the goal is to add a capability

26 Jul 2026

Autonomous Topology Mutation: Safe Runtime Restructuring for Multi-Agent LLM Systems with Capability, State, and Shadow Invariants

arXiv:2607.20488v1 Announce Type: new Abstract: Multi-agent LLM frameworks typically fix their team topology at boot time. When an individual agent becomes overloaded at runtime, for example by mixing

Evaluating Risks in Weak-to-Strong Alignment: A Bias-Variance Perspective

arXiv:2604.25077v2 Announce Type: replace Abstract: Weak-to-strong alignment offers a promising route to scalable supervision, but it can fail when a strong model becomes confidently wrong on examples

Agents

How to write effective AI agent skills: 6 data-backed practices

Three recent studies show what actually makes an AI agent skill effective: human expertise, compact procedures, tight routing, harness-specific testing, and eval-gated changes—not longer Markdown. The

agentsarize-ai

Physics-Informed Deep Learning Model for Cross-Modality Super-Resolution in Fluorescence Microscopy

arXiv:2607.21190v1 Announce Type: new Abstract: Cross-modality image translation offers a route to super-resolution fluorescence microscopy from low-resolution images while reducing phototoxicity and

Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models

arXiv:2607.18695v1 Announce Type: new Abstract: A popular route to interpretable zero-shot classification asks a large language model (LLM) to describe each class name and prompts CLIP with the result

Continual Video-MLLM Adaptation over Evolving Domains

arXiv:2607.18716v1 Announce Type: new Abstract: Video multimodal large language models have shown strong capability in video understanding, yet their adaptation to sequentially evolving domains remain

Counterfactual Reasoning and Environment Design for Active Preference Learning

arXiv:2507.05458v2 Announce Type: replace Abstract: For effective real-world deployment, robots should adapt to human preferences, such as balancing distance, time, and safety in delivery routing. Act

safetyarxiv-cs-ro

Stale but Stable: Staleness-Adaptive Trust Regions for Stabilizing Asynchronous Reinforcement Learning

arXiv:2607.18722v2 Announce Type: replace-cross Abstract: Asynchronous reinforcement learning improves throughput by decoupling rollout generation from optimization, but staleness is an inevitable byp

safetyarxiv-cs-cl

Agents

WASABI: Whole-graph Assignment-based Stabilizer for lAne topology By Inter-frame tracking

arXiv:2607.19781v1 Announce Type: new Abstract: Autonomous driving requires understanding the road as a graph of drivable lanes and their connectivity, beyond the ego lane alone, to follow routes thro

agentsarxiv-cs-cv

One encoder, seven heads: what we learned training a unified security classifier with masked losses [P]

model-releasesr-machinelearning

We spent the last months consolidating seven separate sequence classifiers into one multi-head model, our apex model, so to speak, and since the weights are now public, I wanted to share what worked a

22 Jul 2026

Syntheses

Wiki Lint Report — 2026-07-19

linthealth-checkautomated

Automated lint: 20 errors, 8743 warnings, 3 info

19 Jul 2026

Industrial Dexterity Benchmark: A Hardware-Software Benchmarking Platform for Industrial Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly

16 Jul 2026

Structured Reinforcement Learning for Bayesian Persuasion : Application to Intelligent Interactive Driving

arXiv:2607.13576v1 Announce Type: new Abstract: Interactive driving, wherein an intelligent lead vehicle equipped with real-time traffic data coordinates route choices of connected vehicles, offers a

safetyarxiv-cs-lg

16 Jul 2026

Weight Feedback Computes the Jacobian Transpose Locally in Modern Deep Networks

model-releasesarxiv-cs-lg

arXiv:2607.13380v1 Announce Type: new Abstract: Predictive Coding (PC) offers a biologically motivated alternative to backpropagation via local weight updates, yet routing error between layers still r

16 Jul 2026

It Takes a MAESTRO To Prune Bad Experts

arXiv:2607.08601v1 Announce Type: new Abstract: Sparsely-activated Mixture-of-Experts (MoE) language models achieve remarkable inference efficiency by activating only a small fraction of parameters pe

safetyarxiv-cs-cl

10 Jul 2026

An Hybrid Quantum-Classical Diffusion Model for Image Generation

arXiv:2607.07072v1 Announce Type: new Abstract: Quantum diffusion models provide a physics-consistent route to generative learning by formulating noising and denoising directly on quantum states. Howe

researcharxiv-cs-lg

9 Jul 2026

Prior-matched evaluation of operational Earth-observation classifiers: a three-number reporting method demonstrated on Sentinel-1 internal-wave detection

arXiv:2607.07146v1 Announce Type: cross Abstract: The Internal Waves Service screens the Sentinel-1 Wave-mode archive for internal solitary waves, routing detections to experts whose adjudication time

9 Jul 2026

Solve harder problems with AlphaEvolve, now available to everyone on Google Cloud

model-releasesgoogle-cloud-ai

Many of the most challenging and valuable problems in the world are related to optimization. Now, AI is now making these problems tractable. If you've ever tried to design a microchip, plan a delivery

9 Jul 2026

Securing Amazon Bedrock AgentCore Runtime with AWS WAF

This post shows you two architecture patterns that address this problem. Both use an internet-facing ALB with AWS WAF and route traffic through a VPC Interface Endpoint to AgentCore Runtime. Pattern 1

safetyaws-ml-blog

8 Jul 2026

Adaptive Inference Batching using Policy Gradients

arXiv:2607.05272v1 Announce Type: cross Abstract: Inference serving systems must balance throughput and latency under bursty, heterogeneous workloads, yet the industry standard remains static batching

AViS-Mamba: Adaptive Visual Steering of Audio State-Space Dynamics for Violence Detection

arXiv:2604.03329v2 Announce Type: replace-cross Abstract: Automatic violence detection from video is challenging because violent interactions may be distant, occluded, or only partially visible. Audio

Displacement Preserving Relational Distillation for Robust Medical Segmentation

arXiv:2607.04599v1 Announce Type: new Abstract: Accurate 3D medical segmentation is limited by anatomical variability and high computational costs. While knowledge distillation (KD) offers a route for

safetyarxiv-cs-cv

Pathways of Visual Information Flow in Vision-Language Models

arXiv:2607.03358v1 Announce Type: cross Abstract: We study how visual information is routed in vision-language models (VLMs). Using causal patching on controlled synthetic and natural datasets, we fin

researcharxiv-cs-cl

Streaming Model Cascades for Semantic SQL

arXiv:2604.00660v2 Announce Type: replace-cross Abstract: Modern data warehouses extend SQL with semantic operators that invoke large language models on each qualifying row, making per-row inference o

Towards transferable lightweight neuromorphic computing through a model-free temporal-switch framework

model-releasesarxiv-cs-lg

arXiv:2607.02608v1 Announce Type: cross Abstract: Lightweight neuromorphic computing offers a promising route to efficient AI, with particular benefits for resource-constrained edge deployments. Howev

Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders

arXiv:2607.04487v1 Announce Type: cross Abstract: Neural autoregressive solvers for the Multi-Attribute Vehicle Routing Problem (MAVRP) reach competitive cost but offer no per-step justification, a pr

URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment

arXiv:2607.04688v1 Announce Type: cross Abstract: Synthesis planning aiming to find pathways of reactions for a target molecule is one of the most important and challenging tasks in drug discovery. Re

Local Ai

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection

arXiv:2607.04350v1 Announce Type: new Abstract: Online social media posts provide scalable signals for early depression screening, and recent studies mainly improve pre-classification evidence through

local-aiarxiv-cs-cl

Path-Constrained Mixture-of-Experts

researchapple-ml-research

Sparse Mixture-of-Experts (MoE) architectures route each token through a subset of experts at each layer independently. We propose viewing MoE computation through the lens of expert paths—the sequence

6 Jul 2026

An Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural Networks