Search: “routing”

Iris-3B: Going Beyond the Latent with Pixel-Space Diffusion Training, Conversion and Fine-Tuning

model-releasesarxiv-cs-cv

arXiv:2610.09450v1 Announce Type: new Abstract: Pixel-space diffusion models avoid the lossy VAE of latent models, which suggests an advantage on downstream tasks where fine-grained detail matters. We

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MoR-MLLM: Mixture of Recursions for Efficient Multimodal Large Language Models

DGX agent

arXiv:2610.08830v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across vision and language tasks. However, their massive co

applicationsarxiv-cs-cv

8 Oct 2026

OpenDocRouter is basically OpenRouter for document OCR You can compare and use all your favorite OCR models under a single API / billing int…

OpenDocRouter is basically OpenRouter for document OCR You can compare and use all your favorite OCR models under a single API / billing interface. They range from some of the lightweight/OSS models (

agentsjerry-liu--x

Oracle-Efficient and Parameter-Free Agnostic Smoothed Online Learning

model-releasesarxiv-cs-lg

arXiv:2610.10499v1 Announce Type: new Abstract: Online learning is an attractive framework in many domains because it permits well-defined learning even when data are dependent or chosen adversarially

Steering Follows Geometry, Not Labels: Emotion Directions in a Full-Duplex Speech Model

arXiv:2610.08887v1 Announce Type: new Abstract: Full-duplex voice agents need to modulate emotion and delivery during real-time conversations, when de-escalating a complaint, carrying urgency in dispa

researcharxiv-cs-cl

Towards Accurate End-Effector Localization for UMI-Style Robotic Manipulation Teaching

model-releasesarxiv-cs-ro

arXiv:2610.09857v1 Announce Type: new Abstract: Robot demonstration learning requires accurate and temporally complete end-effector localization during close-range manipulation and camera occlusion. E

3 helpful agent use cases that function like an EA and only require calendar access: 1. Email filter: junk signups go to your agent's email …

3 helpful agent use cases that function like an EA and only require calendar access: 1. Email filter: junk signups go to your agent's email address. It reads everything, and you only get recaps of the

agentsallie-k--miller--x

Adaptive Mean Estimation by In-Context Learning: A Gradient-Flow Analysis

arXiv:2610.07804v1 Announce Type: new Abstract: Prior Fitted Networks (PFNs) such as TabPFN now rival established statistical procedures across prediction and estimation tasks. A natural explanation i

safetyarxiv-cs-lg

Algorithmically Aligned Neural Agglomerative Tree Construction

arXiv:2610.07271v1 Announce Type: new Abstract: Linkage algorithms for hierarchical clustering (HC) are a powerful and efficient framework for constructing clustering trees, yet it is often unclear wh

local-aiarxiv-cs-lg

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

safetyarxiv-cs-ai

CALR: Continuous Anchored Latent Reasoning via Render-of-Thought Compression

arXiv:2610.07175v1 Announce Type: new Abstract: Visual latent reasoning compresses rendered derivations into compact intermediate states, reducing textual reasoning overhead. Existing approaches diffe

researcharxiv-cs-cv

Cascadia: Resident 975B MoE Inference on Eleven AI PCs

arXiv:2610.07219v1 Announce Type: new Abstract: Mixture-of-experts models make nearly trillion-parameter capacity accessible with sparse per-token computation, provided that the serving system can dis

Co-Evolving Paths and Flows via Path-Flow Alignment

arXiv:2610.08717v1 Announce Type: new Abstract: We study path-flow alignment as a unified training objective for flow matching. Instead of fixing the interpolation path and learning only the velocity

safetyarxiv-cs-cv

CoDe-LoRA: Mitigating the Orthogonality Dilemma in Continual Learning of LLMs via Knowledge Consolidation and Decoupling

arXiv:2610.08312v1 Announce Type: new Abstract: Continual learning (CL) is essential for Large Language Models (LLMs) to sequentially adapt to evolving tasks. To mitigate catastrophic forgetting, rece

Compact Robot Policies Need Fine-Grained Visual Representations

arXiv:2610.08183v1 Announce Type: cross Abstract: Multi-task manipulation policies differ in architecture, scale, and pretrained priors all at once, so published comparisons cannot attribute performan

CoRE: Learning Collaboration-Role Experts for Decentralized Collaborative Manipulation with One Policy

arXiv:2610.07752v1 Announce Type: new Abstract: Collaborative manipulation requires robots to perform complementary actions as interactions unfold. We study single-policy decentralized collaboration:

safetyarxiv-cs-ro

DHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning

arXiv:2610.07835v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orch

Do I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents

arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet stru

local-aiarxiv-cs-ai

DTFormer: Text-Guided Semantic Alignment for RGB-D Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.07014v1 Announce Type: new Abstract: RGB-D semantic segmentation has made notable progress by fusing RGB and Depth, yet mainstream models still learn features almost exclusively from pixel-

EMODE: Dynamic Para-Semantic Experts for Emotion-Aware Speech Language Modeling

model-releasesarxiv-cs-cl

arXiv:2610.06956v1 Announce Type: new Abstract: Large speech language models have demonstrated strong capabilities in unified cross-modal understanding and generation, yet paralinguistic cues, especia

Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model Family

model-releasesarxiv-cs-cl

arXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained

FastH3 V2/V3: Project Status

model-releasesr-stablediffusion

https://preview.redd.it/pr5bl6rcezth1.png?width=834&format=png&auto=webp&s=dca7440c56e169b53a586182368829f848805c9a They released FastH3 V2 three weeks ago: https://www.reddit.com/r/StableDiffusion/co

Applications

FluidPD: In-Place Elasticity for SLO-Aware Prefill-Decode Disaggregated LLM Serving

arXiv:2610.06917v1 Announce Type: new Abstract: Prefill-decode disaggregation is becoming a common architecture for LLM serving because it separates two phases with distinct execution patterns and SLO

applicationsarxiv-cs-ai

From Sandbox to Enforcement: Confidence-Qualified Threat Intelligence for Critical Infrastructure

arXiv:2610.07310v1 Announce Type: cross Abstract: Security operations centres and national incident-response teams defending critical infrastructure collect abundant threat data yet struggle to turn i

researcharxiv-cs-ai

Honesty over Accuracy: Trustworthy Language Models through Reinforced Hesitation

arXiv:2511.11500v3 Announce Type: replace Abstract: Modern language models fail a fundamental requirement of trustworthy intelligence: knowing when not to answer. Despite achieving impressive accuracy

researcharxiv-cs-lg

Inference-Time Projection for Physically Valid Biomolecular Diffusion Models

arXiv:2610.07037v1 Announce Type: new Abstract: AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically in

local-aiarxiv-cs-ai

Introducing Google Cloud’s U4 compute: Enabling ultra-low latency trading

model-releasesgoogle-cloud-ai

In capital markets, operational success is built on predictable performance and low latency, where even tiny variations in packet timing alter queue priority and trade execution. At the same time, bot

MemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments

arXiv:2610.07376v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in interactive environments, where they need to make sequential decisions through observation, ac

Metonymic Circuits for Abstract Concept Grounding in Vision Transformers

arXiv:2610.06928v1 Announce Type: new Abstract: We study how Vision Transformers ground abstract concepts (e.g., angry) when training data provide limited direct referential evidence. We hypothesize a

researcharxiv-cs-ai

MoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization

arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse

OpenDocRouter is here! https://www.opendocrouter.ai/ Some time ago, I realized LlamaIndex was really good at benchmarking and applying nearl…

OpenDocRouter is here! https://www.opendocrouter.ai/ Some time ago, I realized LlamaIndex was really good at benchmarking and applying nearly every model to document parsing (see: ParseBench). So, why

agentsjerry-liu--x

PACE: Stage-Consistent Long-Horizon Robot Manipulation via Progress-Aligned Context for Execution

arXiv:2610.07917v1 Announce Type: new Abstract: Demonstration-conditioned policies provide a natural interface for specifying robot behavior, yet long-horizon manipulation remains difficult when visua

safetyarxiv-cs-ro

PHBA: Prefix-State Hybrid Block Attention

arXiv:2610.08527v1 Announce Type: new Abstract: Hybrid architectures combining linear sequence models with softmax attention provide an effective balance between efficient long-context modeling and pr

local-aiarxiv-cs-lg

RadOnc-Agent: An LLM-Orchestrated Framework for AI Workflows Across the Radiotherapy Care Pathway

arXiv:2610.06923v1 Announce Type: new Abstract: Artificial intelligence has advanced individual radiotherapy tasks, yet these capabilities remain separated across clinical stages, software environment

ReGraph: A Computational Account of Emergent Generalization in the 'what' and 'where' Dual Visual Streams

arXiv:2610.07962v1 Announce Type: cross Abstract: Where generalization capacity--the ability to extract context-invariant relational structures--first emerges remains a central question in AI and neur

Rethinking Fine-Tuning: Unlocking Hidden Capabilities in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2512.23073v2 Announce Type: replace-cross Abstract: Fine-tuning has become the dominant paradigm for adapting Vision-Language Models (VLMs), yet most approaches rely on explicit weight updates t

SCOPE: Certified Theorem Proving with a Language Model as the Policy Planner

arXiv:2610.08319v1 Announce Type: new Abstract: In proof assistants such as Lean, a generated proof must pass machine compilation checks, so evaluation needs no human scoring. Direct generation fails

Secure Speculative Decoding for Large Language Models

arXiv:2610.08678v1 Announce Type: cross Abstract: Speculative decoding accelerates inference for a large language model (LLM), referred to as the target model, by first using a smaller model, referred

safetyarxiv-cs-ai

Seeing Through the Displaced Frame: Privileged Noise Distillation for Vision-Force Precision Assembly

model-releasesarxiv-cs-ro

arXiv:2610.07745v1 Announce Type: new Abstract: Pose error in precision assembly can corrupt not only what a robot observes but also the coordinate frame in which it acts. On the FORGE benchmark, the

Semantic Capability Acquisition and Specialization During Vision-Language Model Fine-Tuning

arXiv:2610.07385v1 Announce Type: new Abstract: Fine-tuning vision-language models (VLMs) is typically evaluated at a single downstream checkpoint, obscuring whether a semantic capability was never ac

researcharxiv-cs-cv

SENSE: State-aware Emotion Navigation Storytelling Engine

arXiv:2610.07666v1 Announce Type: cross Abstract: This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating

researcharxiv-cs-ai

Smart Content Ingestion for Generative AI Workloads

arXiv:2610.07091v1 Announce Type: new Abstract: The evolution of machine learning has progressively changed where intelligence resides in an AI system. In conventional machine learning the task, data

Today I’m excited to introduce OpenDocRouter - a unified API for document parsing with the latest frontier and open-weight models. There are…

model-releasesjerry-liu--x

Today I’m excited to introduce OpenDocRouter - a unified API for document parsing with the latest frontier and open-weight models. There are a lot of VLMs and OCR models that can be used for document

Tram-FL: Reducing Communication and Computation Costs through Sequential Model Circulation in Decentralized Federated Learning

arXiv:2610.07859v1 Announce Type: new Abstract: Conventional decentralized federated learning (DFL) often focuses on clients, with each client maintaining a model copy, performing updates individually

researcharxiv-cs-lg

UNREAL: Unifying Retrieval and Long-Context with a Single Model

arXiv:2610.08463v1 Announce Type: new Abstract: Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an en

researcharxiv-cs-cl

Verifying Coordination in Parallel Coding Agents: NP-Bench and a Scheduling Planner

arXiv:2610.07261v1 Announce Type: new Abstract: A team of coding agents can look fine agent by agent yet fail as a team: each passes its own tests while the merged result is broken, and single-agent e

VietBinoculars: A Zero-Shot Approach for Detecting Vietnamese LLM-Generated Text

arXiv:2509.26189v2 Announce Type: replace Abstract: The rapid proliferation of Large Language Models has intensified the challenge of distinguishing LLM-generated text from human writing in non-Englis

researcharxiv-cs-cl

Weight Oracles: Reading Neural Network Weights with Language Models

model-releasesarxiv-cs-lg

arXiv:2610.07334v1 Announce Type: new Abstract: Interpretability methods for neural networks are predominantly reactive: they analyse activations produced during specific forward passes, requiring kno