Search: “inference”

Revisit to Segment: Working Memory Distillation for Reasoning Segmentation

arXiv:2609.34863v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have approached image segmentation by reasoning about visual content and predicting target locations. Their gen

local-aiarxiv-cs-cv

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Research

Routing Without Embeddings: Fast And Interpretable Routing With Regular Expressions

DGX agent

arXiv:2609.34326v1 Announce Type: new Abstract: Large Language Model (LLM) routers commonly rely on neural query embeddings, with larger encoders expected to better capture query intent and difficulty

researcharxiv-cs-lg

29 Sept 2026

Tutorials

RT-Super: Learning Tumor Segmentation from Longitudinal Images and Reports

arXiv:2609.35637v1 Announce Type: new Abstract: Multi-tumor segmentation is important for early cancer detection and allows radiologists to visualize, verify, and understand AI predictions. However, t

tutorialsarxiv-cs-cv

SAGE: Subspace Alignment for Classifier-Free Guidance in Mixture-of-Experts Diffusion Models

arXiv:2609.34525v1 Announce Type: new Abstract: Diffusion Transformers with Mixture-of-Experts (MoE) routing are a leading recipe for scaling generative models. Classifier-Free Guidance (CFG) is essen

Scaling Versatile 3D Assets Editing with a Million-Scale Dataset

arXiv:2609.34271v1 Announce Type: new Abstract: Although recent 3D generative models produce increasingly realistic assets, controllable 3D asset editing remains challenging. Existing methods are limi

Hardware

Scope-WM: Scoped Computation for Efficient Visual World Models

arXiv:2609.33218v1 Announce Type: new Abstract: Visual world models enable robotic planning by predicting future observations, but dense latent-state propagation and sample-intensive trajectory optimi

hardwarearxiv-cs-cv

Seeing the Heat: Synthesizing High-Resolution Wood Thermal Responses from Optical Imagery

arXiv:2609.31737v1 Announce Type: new Abstract: The thermal behavior of wood is a critical factor in advanced material assembly. However, pixel-level thermal analysis remains fundamentally constrained

local-aiarxiv-cs-cv

SelfCue: Making a 3D CT Report Generator Say What It Already Knows

arXiv:2609.31788v1 Announce Type: new Abstract: Progress in 3D CT report generation is usually sought in increasingly sophisticated architectures and larger pools of training data. We find instead tha

Shallow Queries, Mature Values: Depth-Asynchronous Self-Speculation for Looped Transformers

arXiv:2609.34538v1 Announce Type: new Abstract: Looped Transformers reuse a shared block across recurrent depths, making autoregressive decoding expensive because every generated token requires many s

Simulation-Free Learning of GP-SDEs from Irregular Observations

arXiv:2609.33112v1 Announce Type: new Abstract: Gaussian process stochastic differential equations (GP-SDEs) provide a flexible Bayesian model for unknown continuous-time state dynamics with uncertain

Applications

Simultaneous Translation between Sign Languages

arXiv:2609.35608v1 Announce Type: new Abstract: Deaf and hard-of-hearing (DHH) signers cannot converse in real time across different sign languages today: existing sign-to-sign translation systems run

applicationsarxiv-cs-cv

SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving

arXiv:2609.34117v1 Announce Type: new Abstract: Mixture-of-experts (MoE) models activate few experts per token, yet batched decoding can access nearly the entire expert pool, making expert-weight traf

Small transformers track Bayesian evidence for latent common causes via a context-invariant mechanism

arXiv:2609.35161v1 Announce Type: new Abstract: We present an in-depth investigation of how a form of Bayesian reasoning about common causes can emerge as a cross-contextual generalization in small, t

SocialHumanoid: Towards Expressive Humanoid Behavior via One-Step Co-Speech Motion Generation

arXiv:2609.33311v1 Announce Type: cross Abstract: Humanoid robots are increasingly expected to serve as embodied social agents that communicate naturally with humans through face-to-face interaction.

Stabilizing the Dynamic Low-Rank Training

arXiv:2609.32615v1 Announce Type: new Abstract: Training neural networks directly in a low-rank parameterization is an appealing route to reducing memory, compute, and storage simultaneously during bo

Sub-Model Short-Term Memory Convolutions for Keyword Spotting Systems on Device

arXiv:2609.35005v1 Announce Type: cross Abstract: Keyword Spotting (KWS) is becoming increasingly important as voice-controlled devices grow more widespread. While voice interaction with smartphones a

SymDrift: One-Shot Generative Modeling under Symmetries

arXiv:2605.06140v2 Announce Type: replace Abstract: Generative modeling of physical systems, such as molecules, requires learning distributions that are invariant under global symmetries, such as rota

safetyarxiv-cs-lg

SyncRA: Learning Temporal Correspondence in Omni-Modal Models

arXiv:2609.34363v1 Announce Type: new Abstract: Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at th

Task-Aware Discretization of Differentiable Logic Gate Networks

arXiv:2609.33747v1 Announce Type: new Abstract: Differentiable logic gate networks (DLGNs) enable gradient-based training of highly efficient Boolean networks by relaxing discrete logic gates during t

Test-Time Spatial Reasoning for Robot Manipulation Using Generative Real-to-Sim

arXiv:2609.33982v1 Announce Type: cross Abstract: Spatial reasoning is fundamental to general robot intelligence, as it enables robots to complete long-horizon tasks involving multi-object interaction

Thanks to you r/LocalLLaMA, my mom was able to use my app! The open-source app that can watch your screen and trigger actions. It is now easy to use, thanks to your feedback.

model-releasesr-localllama

TL;DR: I'm a solo dev who wanted a simple, private way to have local LLMs watch my screen and do simple logging/notifying. After a year of building, I released v3.0.0 and my mom was able to use it for

The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding

arXiv:2609.31747v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) must balance local detail against scene context when interpreting ultra-high-resolution (UHR) remote sensing (R

The GUI Is Not the State: Diagnosing State Aliasing in GUI World Models

arXiv:2609.32679v1 Announce Type: cross Abstract: GUI World Models (GUI-WMs) are increasingly used to predict future states for agent planning and simulation, yet most existing formulations condition

The Temporal Tug-of-War: Visualizing and Detecting RAG Conflicts in Diffusion Models via Trajectory Variance

arXiv:2609.31684v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) introduces a specific failure mode in discrete diffusion language models: when retrieved context contradicts para

Theory of Scene: Breaking the Symmetry Trap in Multi-Agent LLM Coordination

arXiv:2609.32939v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) are largely homogeneous, as their agents behave alike even across distinct LLMs. We show that

Think Fast, Plan Selectively: Adaptive Deliberation for Efficient Data-Driven MPC

arXiv:2609.32591v1 Announce Type: cross Abstract: Data-driven model predictive control (MPC) combines learned world models with online trajectory optimization, achieving strong performance in continuo

safetyarxiv-cs-lg

Triangular Resampling for Long-Horizon Motion Generation

arXiv:2609.34697v1 Announce Type: new Abstract: We introduce Triangular Resampling (TR), a post-training method for mitigating long-horizon error accumulation in motion diffusion models. Built on Floo

TSGate: Timestep-Aware Gated Attention for Diffusion Transformers

arXiv:2609.34539v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have emerged as the dominant architecture for high-fidelity image and video generation. Recent DiT systems increasingly us

Two-Stage Multi-View Gait Recognition with a Re-Embedding Network

arXiv:2609.32244v1 Announce Type: new Abstract: Gait recognition always remains challenging due to severe overfitting and the rigid view constraints common in single-stage approaches. We propose a two

Typed Temporal Interaction Features for Simulation-Backed Forecasting of Open-Source Game Release Incidents

arXiv:2609.31647v1 Announce Type: new Abstract: Open-source video-game quality depends on inter-actions among code, assets, configuration, tests, contributors, and issue workflows, yet conventional de

local-aiarxiv-cs-lg

Understanding Generalization Requires Universal Induction

arXiv:2609.34458v1 Announce Type: cross Abstract: Classical statistical theory is insufficient to explain the successes of general-purpose AI models, because it depends on handcrafted inductive biases

safetyarxiv-cs-lg

VaME: Exploring Variational Latent Reasoning for Multimodal Embeddings

arXiv:2609.33402v1 Announce Type: new Abstract: Universal multimodal retrieval requires compact embeddings that preserve task-relevant semantic information across diverse modalities. Prior works have

VCRE-Fib: View-Conditioned Regional Evidence for Fine-Grained Ultrasound Grading of Schistosoma japonicum-Associated Liver Fibrosis

arXiv:2609.32840v1 Announce Type: new Abstract: Accurate assessment of Schistosoma japonicum-associated liver fibrosis is essential for disease management and long-term follow-up in endemic regions. U

local-aiarxiv-cs-cv

Verifying the Linear Representation Hypothesis: How Interpretable Are Vision SAEs?

arXiv:2609.35020v1 Announce Type: new Abstract: Vision Sparse Autoencoders (SAEs) have become a popular tool in Mechanistic Interpretability due to their presumed ability to disentangle complex featur

Tutorials

VGGT-Diff: Visual Geometry Meets Diffusion for Sparse-View Novel View Synthesis

arXiv:2609.33253v1 Announce Type: new Abstract: We present VGGT-Diff, a geometry-routed multi-view diffusion model for sparse-view novel view synthesis. Existing novel view synthesis (NVS) methods fac

tutorialsarxiv-cs-cv

Applications

Video Captioning in Low-Light Conditions through Efficient Uncertainty-Aware Caption Correction

arXiv:2609.31697v1 Announce Type: new Abstract: Low-light conditions can significantly degrade the ability of vision-language models (VLMs) to accurately describe human actions in videos. In this work

applicationsarxiv-cs-cv

VideoPhysEdit: Physical Counterfactual Video Editing via Rigid-Body Physical Scene Reconstruction

arXiv:2609.35134v1 Announce Type: new Abstract: Video editing has advanced substantially in recent years, with methods increasingly accounting for the visual consequences of edits, such as changes to

What does FFN compression change downstream? Same-state causal restoration in diffusion language models

arXiv:2609.31685v1 Announce Type: new Abstract: Diffusion language models (DLMs) enable flexible, parallel generation, but their iterative denoising remains computationally expensive, motivating incre

local-aiarxiv-cs-lg

What Next-Event Accuracy Cannot See: Closed-Loop Evaluation of Emergency Department Trajectory Simulators

arXiv:2609.31635v1 Announce Type: new Abstract: Clinical trajectory models are usually evaluated by next-event accuracy on observed histories. Simulation is different: models must condition on their o

When Does Structured Knowledge Help Neural Theorem Proving?

arXiv:2609.34460v1 Announce Type: cross Abstract: Does structured mathematical knowledge help LLMs prove theorems in Lean 4? If so, for which models, and does the answer vary by problem? Formal librar

When Helpful Text Hurts: Option-Redirecting Bias in Vision-Language Models

arXiv:2609.32489v1 Announce Type: cross Abstract: In tri-modal visual question answering (VQA), auxiliary text is commonly used to complement visual and textual inputs, yet its reliability is often un

When Is an SAE Feature Interpretable? A Validation Ladder for EEG Foundation Models

arXiv:2609.34091v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose dense model activations into discrete latents, making individual features easy to interpret--and easy to misinterpr

Where Does the Watermark Hide? Push-Pull Disentanglement for Invisible Watermark Removal

arXiv:2609.31722v1 Announce Type: new Abstract: Fixed image distortions do not cover an attacker that learns from paired clean and watermarked images. We study this paired-training threat with single-

Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation

arXiv:2603.01375v2 Announce Type: replace-cross Abstract: Test-time policy adaptation for multi-turn interactions (T2PAM) is essential for aligning Large Language Models (LLMs) with dynamic user needs

WorldGuide: Learning Success-Failure Boundaries in Latent World Models for Vision-Language-Action Policies

arXiv:2609.34206v1 Announce Type: new Abstract: Latent world models offer a promising way to improve Vision-Language-Action policies by capturing the consequences of actions. However, models trained p

Write Back the Delta: Revisiting the Same Tokens with Fresh Representations

arXiv:2609.32457v1 Announce Type: new Abstract: Transformers process information strictly forward through depth, preventing deeper computation from revisiting and refining earlier representations. To

Zero-Shot Reactive Obstacle Avoidance for Generative Robot Policies

arXiv:2609.35231v1 Announce Type: new Abstract: We propose NUDGE (Nudge Update via Differentiable GEometry), a training-free obstacle-avoidance procedure that can be incorporated in any robot policy b

safetyarxiv-cs-ro

Accounting for Bias Enables Sustainable LLM Evaluation