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arXiv:2609.22500v1 Announce Type: new Abstract: Autonomous navigation requires precise and efficient semantic segmentation, yet existing frame-based approaches remain limited by motion blur, glare, la

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Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargons

DGX agent

arXiv:2505.16227v4 Announce Type: replace Abstract: Personalizing jargon detection and explanation is essential for making technical documents accessible to readers with diverse disciplinary backgroun

model-releasesarxiv-cs-cl

22 Sept 2026

Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

model-releasesarxiv-cs-lg

arXiv:2609.24358v1 Announce Type: new Abstract: Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper prop

Fathom-Vaidya: Advancing Medical Reasoning with Rubric-Based Rewards

model-releasesarxiv-cs-cl

arXiv:2609.24480v1 Announce Type: cross Abstract: Deploying Large Language Models (LLMs) in healthcare requires robust performance across two complementary dimensions - diagnostic reasoning: the conve

FLARE: A Full-Lifecycle Dense Supervision Paradigm for Long-Horizon Coding Agents via Generative Reward Model

arXiv:2609.23808v1 Announce Type: new Abstract: While test-time scaling enhances Large Language Model (LLM) agents in long-horizon software engineering (SWE), sparse binary rewards (Pass/Fail) create

safetyarxiv-cs-cl

FlockDiffusion: Assignment-Conditioned Diffusion for Multi-Drone Task Allocation and Completion

model-releasesarxiv-cs-ro

arXiv:2609.23745v1 Announce Type: new Abstract: Autonomous multi-drone navigation requires fleets to service distributed objectives in cluttered environments under tight computational budgets. Efficie

Applications

Generalized Multimodal Foundation Model

arXiv:2609.22107v1 Announce Type: cross Abstract: Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefin

applicationsarxiv-cs-cl

Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models

arXiv:2609.24879v1 Announce Type: new Abstract: Counterfactual image generation answers questions about how a subject would have looked under retrospective, hypothetical scenarios. Recent methods have

Tools

GPT-6 Luna is half the price of 5.6 Luna, which was already an astonishingly cheap model given how capable it is Luna is my favorite model f…

GPT-6 Luna is half the price of 5.6 Luna, which was already an astonishingly cheap model given how capable it is Luna is my favorite model for building product features thanks to its cost (and speed)

toolssimon-willison--x

Industry

GPT-6 Sol and Luna are great models but also these characters are so cute

GPT-6 Sol and Luna are great models but also these characters are so cute Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, br

industrysam-altman--x

HOIBlender: Blending Lightweight Detection with Vision-Language Priors for Efficient Human-Object Interaction Detection

arXiv:2609.23431v1 Announce Type: new Abstract: Human-object interaction (HOI) detection requires grounding an interacting human-object pair and recognizing the verb that links them, often under sever

Agents

holy fuck it's christmas

holy fuck it's christmas Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more

agentsjerry-liu--x

If You Hear It, Help Find It: Orthogonal Knowledge Distillation for Open-Vocabulary Audio-Visual Event Localization

arXiv:2609.23376v1 Announce Type: cross Abstract: Open-vocabulary audio-visual event localization (OV-AVEL) grounds a text-queried event in time from video, audio, and language. The supervision source

INTCORT: Training-Free Spatial Reasoning Enhancement for Vision-Language Models via Input Transformations and Confidence Routing

arXiv:2609.24813v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in multimodal tasks, yet they still exhibit poor ability in spatial reasoning. E

Layer-Aware Position Embeddings for Visual Token Pruning in Multimodal Large Language Models

arXiv:2609.23715v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) incur substantial computational overhead due to the reliance on hundreds of visual tokens to represent images.

Applications

Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds

arXiv:2609.23915v1 Announce Type: cross Abstract: This paper presents an end-to-end framework for reconstructing overhead power utility network topology and extracting span-level physical metadata fro

applicationsarxiv-cs-cv

Learning Beyond What Humans Can Demonstrate

arXiv:2609.24996v1 Announce Type: new Abstract: Behavior cloning for robot manipulation relies on expert demonstrations. However, for tasks that require dynamic stability, precise contact timing, or d

Linguistic Features for Interpretable Textual Entailment

arXiv:2609.24932v1 Announce Type: new Abstract: Despite the success of neural models in natural language processing, their black-box nature limits interpretability and conceals the linguistic phenomen

safetyarxiv-cs-cl

Look Where It Counts: A Free, Label-Free Visual Evidence Signal for Fine-Grained Vision-Language Reasoning

arXiv:2609.24244v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) fail at fine-grained visual questions less because they cannot reason than because they never see the evidence:

Manipulation Feasible Navigation Among Movable Obstacles with Discrete Contact Pushing

arXiv:2609.23312v1 Announce Type: new Abstract: In environments with large movable obstacles, detour-only navigation can be inefficient or even infeasible, while obstacle interaction requires reasonin

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

Model-Agnostic Feature Selection via LOCO-Guided Adaptive Minipatch Sampling

arXiv:2609.24126v1 Announce Type: cross Abstract: Black-box machine learning models increasingly deliver strong predictions, but extracting useful information from them, such as a set of important fea

Moonworks Lunara: Modeling Artistic Intelligence

arXiv:2609.22272v1 Announce Type: new Abstract: We formulate Artistic Intelligence as exploration driven world realization, leaving space for creative possibility while preserving the semantic, artist

MTMed3D: A Multi-Task Transformer-Based Model for 3D Medical Imaging

arXiv:2511.12373v2 Announce Type: replace-cross Abstract: In the field of medical imaging, AI-assisted techniques such as object detection, segmentation, and classification are widely employed to alle

Multiple latent orderings better predict language model preferences

arXiv:2609.22170v1 Announce Type: cross Abstract: Language models are frequently employed in settings where they are asked to make value judgments and choices. These observed choices often exhibit int

safetyarxiv-cs-cl

NLPCC 2026 Task 10: Citation-Level Faithfulness Verification with DeBERTa Ensembles and Class-Wise Calibration

arXiv:2609.22774v1 Announce Type: new Abstract: This paper presents our system for Track 2 of the NLPCC 2026 Shared Task 10 on citation-level faithfulness in AI-assisted scientific reporting. Given an

researcharxiv-cs-cl

Observational Equivalence of LLM and Human Annotation

arXiv:2609.22133v1 Announce Type: new Abstract: In this paper, we show that LLM and human coding are observationally equivalent in terms of annotation quality: recent LLMs agree with expert coders at

researcharxiv-cs-cl

Observing and Controlling Features in Vision-Language-Action Models

arXiv:2603.05487v2 Announce Type: replace Abstract: Vision-Language-Action models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that

One Patch, Three Roles: What Is Actually Coupled in Autoregressive Time-Series Forecasting?

arXiv:2609.23686v1 Announce Type: new Abstract: Patch-based autoregressive time-series forecasting often ties input representation, learned transitions, and recursive execution to one patch length. We

PETR: Prompt Ensembling with Training-free Routing for Vision-Language Models

arXiv:2609.23600v1 Announce Type: new Abstract: Prompt learning efficiently adapts vision-language models (VLMs) to downstream tasks, but gains on seen classes often come at the expense of generalizat

Agents

Physical-Touch Observability from Wrist Wrench in Granular Scooping

arXiv:2609.22852v1 Announce Type: new Abstract: Mining and earthmoving are important real-world deployment settings for embodied intelligence. Autonomous transport and driving systems have improved su

agentsarxiv-cs-ro

Planning-Aligned Pretraining of BEV Representations with Sparse Action-Conditioned Targets for End-to-End Autonomous Driving

arXiv:2609.22868v1 Announce Type: new Abstract: End-to-end driving requires planning-relevant bird's-eye-view (BEV) representations, but existing pretraining approaches often rely on task annotations

Planning and Rendering in Concert: DeepFusion of Autoregressive Layouts and Diffusion for Visual Text Generation

arXiv:2609.22916v1 Announce Type: new Abstract: Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit lay

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of…

Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to sup

model-releasesopenai--x

PosEviLoc: Position-Conditioned Spatial Evidence for Language-Based 3D Localization

arXiv:2609.23534v1 Announce Type: new Abstract: Language-based 3D localization retrieves the point-cloud submap containing a target position from descriptions of nearby objects and their spatial relat

Hardware

PREM: Prefix-Steered Recurrent Memory for Long-Video Understanding

arXiv:2609.23601v1 Announce Type: new Abstract: Long-video understanding must capture transient visual evidence under strict token budgets, yet existing methods compress frames, append memory tokens,

hardwarearxiv-cs-cv

ProxyBuild: Text-Guided Structured 3D Building Generation with Mesh-Anchored Procedural Proxies

arXiv:2609.23386v1 Announce Type: new Abstract: Text-guided 3D building generation holds tremendous application potential, yet existing generative models typically output inseparable single meshes or

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

arXiv:2607.14293v2 Announce Type: replace-cross Abstract: Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge ju

Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networks

arXiv:2609.23141v1 Announce Type: cross Abstract: Real time plasma state estimation for control of Tokamak devices are challenging due to the stringent latency requirements of the plasma control syste

Agents

Relationally Grounded Latent World Models for Autonomous Driving

arXiv:2609.24626v1 Announce Type: new Abstract: Latent world models learn predictive representations for autonomous driving, but the relational semantics these states preserve often remain implicit. W

agentsarxiv-cs-cv

Representation-guided in-context learning for medical image interpretation with multimodal large language models

model-releasesarxiv-cs-cl

arXiv:2609.24057v1 Announce Type: cross Abstract: Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires re

Rethinking Streaming Video Diffusion Model: Context, Execution, and Training

arXiv:2609.22283v1 Announce Type: new Abstract: Understanding the design space of streaming video diffusion is essential to exploring its potential for generation quality and computational efficiency.

Run GGUF models directly with transformers. This work brings ggml's Metal kernels to the transformers ecosystem, increasing compatibility an…

model-releasesgeorgi-gerganov--x

Run GGUF models directly with transformers. This work brings ggml's Metal kernels to the transformers ecosystem, increasing compatibility and performance. More info below Millions of GGUF downloads la

SafeTune: A Unified Faithful Library for Auditing and Repairing Safety Drift in Fine-Tuned LLMs

arXiv:2609.22153v1 Announce Type: new Abstract: Methods for addressing safety drift in fine-tuned Large Language Models (LLMs) are scattered across incompatible implementations, lifecycle stages, and

safetyarxiv-cs-lg

Applications

SegTSim: A Big Data Driven Segmented Temporal Simulation Framework for Heterogeneous Multivariate Systems

arXiv:2609.22192v1 Announce Type: new Abstract: Heterogeneous multivariate time-series systems exhibit segment-specific nonlinear dynamics that challenge monolithic forecasting architectures. We propo

applicationsarxiv-cs-lg

ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving

arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m

local-aiarxiv-cs-lg

SewFusion: Tailored Generation of Topology and Panel-Level Geometry for Sewing Patterns

arXiv:2609.23548v1 Announce Type: new Abstract: Generating sewing patterns from images and text requires modeling a heterogeneous representation composed of discrete topology and continuous geometry.

Shared Execution-Clock Drifting Policy for Dynamic Precision Manipulation

arXiv:2609.23305v1 Announce Type: new Abstract: Manipulation under time constraints requires both accurate actions and an execution rhythm that matches the evolving scene. This becomes critical when a