Search: “framework”

Train Where the Quantized Model Goes: On-Policy Distillation for Low-Bit Reasoning

arXiv:2609.26708v1 Announce Type: new Abstract: Quantization-aware distillation (QAD) restores much of the short-form question-answering performance lost to sub-3-bit quantization, yet leaves mathemat

safetyarxiv-cs-lg

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Transport-Coupled Bayesian Flows for Molecular Graph Generation

DGX agent

arXiv:2510.10211v4 Announce Type: replace Abstract: Molecular graph generation (MGG) is essentially a multi-class generative task, aimed at predicting categories of atoms and bonds under strict chemic

model-releasesarxiv-cs-lg

23 Sept 2026

TSS: Target-Side Sparsification for Speculative Decoding in Domain-Specific Large Language Models

arXiv:2609.26100v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference through collaboration between a lightweight draft model and a target verifier. Existing

TTTIR: Unlocking Instance-Specific State Evolution via Test-Time Training for Image Restoration

arXiv:2609.26151v1 Announce Type: cross Abstract: Image restoration is inherently challenging due to the diverse and highly input-dependent nature of real-world degradations. While recent architecture

applicationsarxiv-cs-cv

TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculum

arXiv:2609.25864v1 Announce Type: cross Abstract: Visual object removal can eliminate a target from video frames, yet its acoustic trace persists in the soundtrack, causing obvious audio-visual incons

Hardware

Uncertainty-Aware 3D Residual Wavelet Diffusion for Ultra Low-Field MRI Super-Resolution

arXiv:2609.25319v1 Announce Type: new Abstract: Ultra low-field MRI expands global access to neuroimaging but produces scans with low signal-to-noise ratio, reduced contrast, and thick slices. While r

hardwarearxiv-cs-cv

Video-HopChain: Multi-Hop Questions and Confidence-Gated Exploration for Video Reasoning Models

arXiv:2609.25773v1 Announce Type: new Abstract: HopChain has shown on still images that multi-hop data synthesis improves vision-language reasoning, because long chain-of-thought reasoning exposes err

Vision-Language Models as copilots for Autonomous UAV Navigation: Analysis of Latency and Reliability in Degraded Environments

model-releasesarxiv-cs-ro

arXiv:2609.26084v1 Announce Type: new Abstract: The integration of Vision-Language Models (VLMs) in autonomous Unmanned Aerial Vehicles (UAVs) offers unprecedented semantic reasoning capabilities. How

VLM-in-Sandbox: Visual Workspaces for Agentic Visual Reasoning

model-releasesarxiv-cs-ai

arXiv:2609.24362v1 Announce Type: new Abstract: Sandboxed computer environments support multi-step reasoning with tools, executable programs, and persistent files, yet their extension from language mo

Vorch-Human: Unified Multi-Task Human-Centric Generation via Long-Horizon Continuation

arXiv:2609.26117v1 Announce Type: new Abstract: Human-centric audio-visual generation spans several closely related tasks: animating a person from driving speech, jointly generating speech and video f

When Point Clouds Outperform Pixels: Rethinking Zero-Shot Multimodal Anomaly Detection

arXiv:2609.25793v1 Announce Type: new Abstract: Zero-shot multimodal anomaly detection commonly assumes that RGB and point cloud modalities are equally reliable and can contribute uniformly to anomaly

Hardware

When Riemann flows with Wasserstein: Generative Modeling of Probability Distributions on Manifolds

arXiv:2609.25659v1 Announce Type: new Abstract: Many scientific datasets, such as molecular conformational ensembles or single-cell tissue measurements, are naturally modeled as meta-distributions: di

hardwarearxiv-cs-lg

When Scaling Fails: Mitigating Audio Perception Decay of LALMs via Multi-Step Perception-Aware Reasoning

model-releasesarxiv-cs-ai

arXiv:2603.02266v2 Announce Type: replace-cross Abstract: Test-Time Scaling has shown notable efficacy in addressing complex problems through scaling inference compute. However, within Large Audio-Lan

You Should Be Properly Scoring Your Odometry

arXiv:2609.25900v1 Announce Type: new Abstract: When we evaluate the performance of our odometry, it is common practice to score the estimated track against a ground truth. Unfortunately, scoring uses

applicationsarxiv-cs-ro

Zephyron: Integrated Design and Analytical Evaluation of a Solar-Assisted Mobile Manipulator for Multimodal Environmental Reconnaissance and Distributed Visual Inference

arXiv:2609.25709v1 Announce Type: new Abstract: Environmental reconnaissance needs mobile platforms that carry sensors, preserve measurement context, and return interpretable evidence under limited en

safetyarxiv-cs-ro

0.5%>100%: Bidirectional Reciprocal Learning for Referring Image Segmentation

arXiv:2609.24510v1 Announce Type: new Abstract: Recent advances in vision foundation models (VFMs) have shown remarkable capabilities across diverse unimodal visual tasks. However, adapting VFMs to re

3D-MoE: Towards Spatial Intelligence with Mixture-of-Experts for 3D Reasoning and Action Generation

arXiv:2501.16698v2 Announce Type: replace Abstract: Spatial intelligence, encompassing 3D perception and reasoning, is the essential next frontier of AI. Scaling current 3D vision-language models (VLM

researcharxiv-cs-cl

A Hybrid Quantum Neural Network to Analyse Big Experimental Powder X-ray Diffraction Data

arXiv:2609.22376v1 Announce Type: cross Abstract: Quantitative analysis of experimental powder X-ray diffraction data remains challenging when evaluating complex multiphase materials and noisy measure

applicationsarxiv-cs-lg

A Recipe for Efficient Sim-to-Real Transfer in Manipulation with Online Imitation-Pretrained World Models

arXiv:2510.02538v2 Announce Type: replace Abstract: We are interested in solving the problem of imitation learning with a limited amount of real-world expert data. Existing offline imitation methods o

applicationsarxiv-cs-ro

A Red-Team Study of Anthropic Fable 5 & Opus 4.8 Models

arXiv:2606.18193v2 Announce Type: replace-cross Abstract: We evaluate the adversarial robustness of three frontier large language models (LLMs) developed by Anthropic, Opus 4.8, Fable 5 and its succes

safetyarxiv-cs-cl

A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents

arXiv:2601.12538v2 Announce Type: replace-cross Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) de

agentsarxiv-cs-cl

A Tunable Despeckling Neural Network Stabilized via Diffusion Equation

arXiv:2411.15921v3 Announce Type: replace Abstract: The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural net

applicationsarxiv-cs-cv

A Tutorial on Prompt Engineering: From Messy Thoughts to AI Workflows

arXiv:2609.22249v1 Announce Type: new Abstract: This paper treats prompt engineering as a discipline for turning informal human intent into structured AI work specifications. It develops the practice

agentsarxiv-cs-cl

A^2Safe: Counterfactual Evidence-Aligned Adaptive Agent Collaboration for Safe and Effective Visual Question Answering

arXiv:2609.24098v1 Announce Type: new Abstract: Visual Question Answering (VQA) with Multimodal Large Language Models (MLLMs) requires not only producing safe and effective responses, but also groundi

safetyarxiv-cs-cv

AdaMem: Adaptive Memory Token Allocation for Soft Compression in Retrieval-Augmented Generation

arXiv:2609.22100v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language models with retrieved evidence, but processing many long passages is costly and can introduce dis

researcharxiv-cs-cl

AdaptiveCDM: Source-Free Few-Shot Domain Adaptation for Cell Detection in Microscopic Images

arXiv:2503.03370v3 Announce Type: replace Abstract: Cross-domain cell detection for microscopic images suffers from performance degradation due to distribution shifts across imaging domains. Unsupervi

An Efficient and Effective Watermarking Scheme for the Protection of the Intellectual Property Rights of Video Generative Models

arXiv:2609.23586v1 Announce Type: new Abstract: The rapid development of video generative models (VGMs) has enabled the generation of highly realistic synthetic videos, raising concerns about the inte

An Empirical Study and Open Testbed for Federated Fine-Tuning of Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.22973v1 Announce Type: new Abstract: Adapting a pretrained Vision-Language-Action (VLA) model to a new robot, environment, or task requires demonstrations that are collected locally and oft

An Evolutionary Agentic Approach for Open-ended Image Quality Perception

arXiv:2609.22942v1 Announce Type: new Abstract: Generative models are rapidly expanding image quality assessment (IQA) beyond traditional fidelity factors to emerging dimensions such as physical plaus

safetyarxiv-cs-cv

Anatomically Faithful Artifact Suppression in SENSE Accelerated Brain MRI

arXiv:2609.22390v1 Announce Type: cross Abstract: Background: Four-fold accelerated sensitivity encoding (SENSE4) can shorten brain MRI acquisition time but may amplify noise and result in residual al

Anatomy-Decomposed Chest Computed Tomography (CT) Projections as Scalable Supervision for Bone Suppression in Chest Radiographs

arXiv:2609.24937v1 Announce Type: new Abstract: Bone overlap can obscure abnormalities in chest radiographs, while scarce paired training data limit supervised bone suppression. We address this challe

AniPrO: Interpretable Anime Image Provenance Detection via Multi-Dimensional Semantic Reasoning

arXiv:2609.23345v1 Announce Type: new Abstract: As generative AI becomes increasingly used in anime-style image creation, distinguishing human-drawn, AI-inpainted, and text-to-image images is importan

AquaCap: A Training-Free Underwater Embodied Agent with Code-as-Policy

model-releasesarxiv-cs-ro

arXiv:2609.23133v1 Announce Type: new Abstract: Recent advances in vision-language-action models have stimulated growing interest in underwater embodied intelligence. However, their reliance on large-

AskQE: Question Answering as Automatic Evaluation for Machine Translation

arXiv:2504.11582v3 Announce Type: replace Abstract: How can a monolingual English speaker determine whether an automatic translation in French is good enough to be shared? Existing MT error detection

Assessing Readability with LLMs: The Role of Reasoning and Few-Shot Prompting

arXiv:2609.24650v1 Announce Type: new Abstract: Readability assessment is essential for tailoring texts to intended audiences across educational, healthcare, and information retrieval domains. However

Audio-based UAV Localization with Adaptive Temporal Correspondence via Reinforcement Learning

arXiv:2609.24218v1 Announce Type: new Abstract: Audio-based localization provides a low-cost and illumination-independent sensing solution for anti-UAV early warning. However, existing methods typical

researcharxiv-cs-ro

Authority-Preserving Evaluation of Medical Vision-Language Assistants

arXiv:2609.22302v1 Announce Type: new Abstract: Medical vision-language models can propose how urgently a skin lesion should be reviewed, but the local service retains authority to accept or replace t

AutoGym: Blueprint-First Generation of Verifiable Agent Gyms

arXiv:2609.22592v1 Announce Type: cross Abstract: Training agents with reinforcement learning requires a gym, comprising a task, an executable environment in which the task can be attempted, and a ver

agentsarxiv-cs-lg

Automatic multimodal UX improvement recommendations from LLM agent user simulations

arXiv:2609.22971v1 Announce Type: new Abstract: Evaluating user experience (UX) on live websites through user testing is expensive, subjective, and difficult to scale. LLM agents offer a promising rou

agentsarxiv-cs-cl

BadWAM: When World-Action Models Dream Right but Act Wrong

arXiv:2607.15207v2 Announce Type: replace Abstract: World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representat

safetyarxiv-cs-lg

Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting

arXiv:2609.22885v1 Announce Type: new Abstract: Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates pro

safetyarxiv-cs-ro

Local Ai

BarrierFormer: Transformer-Guided Predictive Barrier Enforcement for Safe Robot Control

arXiv:2609.23896v1 Announce Type: new Abstract: Control barrier functions (CBFs) have become one of the most popular tools for encoding and enforcing state constraints in safety-critical robotics. Sta

local-aiarxiv-cs-ro

Beetle: A Bilingual Model Suite for Modelling Second-Language Processing

arXiv:2609.22633v1 Announce Type: new Abstract: Bilingual language models (LMs) offer a controlled setting for studying how training conditions shape second-language (L2) behaviour, but prior work typ

safetyarxiv-cs-cl

Beyond Appearance Shifts: Task-Semantic Action Calibration for VLA Models

model-releasesarxiv-cs-lg

arXiv:2609.23650v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still lack a clear mechanism to balance behavioral

Beyond Emotion Prompts: Fine-Grained Text-to-Image Generation Driven by Valence-Arousal-Dominance

arXiv:2609.24215v1 Announce Type: new Abstract: Although text-to-image models can accurately depict subjects and scenes, creators still struggle to specify the fine-grained emotions an image should co

safetyarxiv-cs-cv

Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs

arXiv:2609.22977v1 Announce Type: cross Abstract: Similarity-based retrieval is the dominant rule for conditioning large language models (LLMs) in in-context learning, retrieval-augmented generation,

Beyond the Text: Verifying That Agent-Written Papers Are Backed by Their Artifacts

arXiv:2609.22111v1 Announce Type: new Abstract: Large language model agents are increasingly capable of conducting research autonomously, producing research documents alongside the code and experiment

Beyond Uniform Subspaces: Spectrum-Aware and Depth-Adaptive Fusion for Multi-Task Model Merging

arXiv:2609.24612v1 Announce Type: new Abstract: Model merging aims to consolidate multiple task-specific models without access to extra training process. However, existing subspace-based methods large