Search: “framework”

SE-ADD: Self-Evolving Audio Deepfake Detection with Mistake-Driven Supervision

arXiv:2609.39679v1 Announce Type: cross Abstract: Audio deepfake detection (ADD) must remain effective when new spoofing attacks emerge after deployment. Emerging audio language model (ALM)-based ADD

researcharxiv-cs-lg

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Tutorials

Seeing as Humans Do: Learning from Motion to Segment Anything Without Supervision

DGX agent

arXiv:2609.39785v1 Announce Type: new Abstract: The Segment Anything Model (SAM) relies heavily on massive manual annotations, creating a fundamental bottleneck for model scaling. While unsupervised m

tutorialsarxiv-cs-cv

1 Oct 2026

Self-Evolving Algorithm-Design Agents: Escaping In-Context Evolutionary Stagnation via Population-Curated Policy Optimization

arXiv:2609.38757v1 Announce Type: new Abstract: Large language models are increasingly participating in complex real-world tasks in the form of algorithm-design agents, designing and refining algorith

Self-Evolving Harness on Multiple Tasks with the Agent as Its Own Optimizer

arXiv:2609.38372v1 Announce Type: new Abstract: A harness is the code around a language-model agent that organizes prompts, calls tools, manages context, and controls execution. As models grow stronge

Semantic Chunking and the Entropy of Natural Language

arXiv:2602.13194v3 Announce Type: replace-cross Abstract: Humans and large language models can predict next letter or word from its prior context much better than random guessing, indicating strong re

ShieldCLIP: Selective Safety Alignment for Harmful Content Mitigation in Multimodal Foundation Models

arXiv:2609.39688v1 Announce Type: cross Abstract: Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment

SimEX: Simulation-Integrated Robotics AutoResearch

arXiv:2609.38982v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital wo

Simon-SR: Spatially Adaptive Modulation and Visual Prompt Adaptation for Text-Reinforced Super-Resolution

arXiv:2607.09351v2 Announce Type: replace Abstract: Severe downsampling makes single image super-resolution (SISR) an ill-posed problem, in which the language-guided multi-modal methods are especially

Agents

SimTrace: Grounded Multimodal User Trajectories Generation for Online User Modeling

arXiv:2609.38397v1 Announce Type: new Abstract: Virtual clients offer a cost-effective approach to support applications such as A/B testing, recommender system development, and interface evaluation. H

agentsarxiv-cs-ai

Social-WM: Safety-Aware Latent World Models for Robot Social Navigation

arXiv:2609.40177v1 Announce Type: new Abstract: Safe social navigation requires a robot to anticipate not only the future consequences of its actions, but also whether a nominal action can actually be

safetyarxiv-cs-ro

Soft Spatial Reasoning

arXiv:2609.38717v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) commonly perform spatial reasoning through chain-of-thought (CoT), encoding intermediate reasoning as autoregress

Hardware

Sparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination

arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and

hardwarearxiv-cs-ai

Spatial-Temporal Multi-scale Network for Screen Content Video Quality Enhancement

arXiv:2609.39894v1 Announce Type: new Abstract: Different from natural videos, Screen Content Videos (SCVs) are characterized by abrupt motion, scene switches, and high-frequency details such as text

Local Ai

SpatialCORE: Confidence-Aware Grounded Spatial Reasoning in Large Vision--Language Models

arXiv:2609.38716v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have made remarkable progress across visual perception tasks, yet spatial reasoning remains a persistent weakness

local-aiarxiv-cs-ai

Tutorials

SPOON: Towards Coherent Compositional 3D Scene Generation from Uncalibrated Multi-view Images

arXiv:2609.39590v1 Announce Type: new Abstract: Compositional 3D scene generation aims to recover complete 3D object shapes and their spatial arrangement from visual observations. Recent image-conditi

tutorialsarxiv-cs-cv

Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models

arXiv:2609.39091v1 Announce Type: cross Abstract: Inference-time alignment of flow and diffusion-based models is critical for achieving flexible generative modeling. Theoretically, Doob's h-transform

safetyarxiv-cs-lg

SteerQuant: Steering Quantization Error with Action-Guided Scaling in World-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.39056v1 Announce Type: new Abstract: World-action models (WAMs) jointly generate future world states and actions through iterative denoising, using shared weights to process heterogeneous s

StreamRig: Exploiting Intra-Rig Geometry for Streaming Multi-Camera Odometry

model-releasesarxiv-cs-cv

arXiv:2609.40244v1 Announce Type: new Abstract: Mobile robots and vehicles carry synchronized multi-camera rigs, yet many streaming 3D foundation models are designed for monocular input, leaving effic

Structure-aware Reinforcement Learning for Protein Directed Evolution

arXiv:2609.39048v1 Announce Type: cross Abstract: Protein optimization remains a longstanding goal in life sciences. Existing machine learning-assisted directed evolution (MLDE) methods primarily rely

Structure of Basic Human Values in Russian Social Media

model-releasesarxiv-cs-cl

arXiv:2603.18822v2 Announce Type: replace Abstract: What is known about the values of national populations rests almost entirely on questionnaires, which prompt respondents to rate researcher-supplied

Switching Linear Attention

arXiv:2609.39034v1 Announce Type: cross Abstract: Designing expressive sequence layers with efficient inference remains a central challenge in modern machine learning. Standard softmax attention achie

SynIL: Leveraging Synergy for Offline Imitation Learning from Imperfect Demonstration Datasets

arXiv:2609.38225v1 Announce Type: cross Abstract: Imitation learning enables robots to acquire complex skills directly from massive demonstration datasets, but its performance degrades severely when d

T-ARC: Topology-Aware Randomized Clustering via Distributionally Robust Stochastic Block Models

model-releasesarxiv-cs-lg

arXiv:2609.39466v1 Announce Type: new Abstract: In this work, we introduce a new clustering method, namely T-ARC (Topology-Aware Randomized Clustering), that corrects the geometric bias of K-means by

Tutorials

TACIT: Optimization Models that Learn from Their Mistakes

arXiv:2609.38434v1 Announce Type: cross Abstract: Real-world optimization problems are difficult to model accurately because many objectives and constraints reside in domain experts' tacit knowledge,

tutorialsarxiv-cs-ai

Local Ai

TACTIC: Temporal and Context-Aware LLM Tactical Planning for Roadside LiDAR Attacks

arXiv:2609.39969v1 Announce Type: cross Abstract: Physical LiDAR attacks are often evaluated using fixed primitives and manually selected parameters, despite their strong dependence on surrounding tra

local-aiarxiv-cs-ai

Tactile Curiosity Drives Robot Interaction

arXiv:2609.40134v1 Announce Type: cross Abstract: Mastering robot manipulation skills via reinforcement learning (RL) remains largely sample-inefficient. The most common RL algorithms rely on random a

Agents

TAGGRAPH: Tag-Augmented Graphs for Graph Retrieval of Agent Persistent Histories

arXiv:2609.38353v1 Announce Type: cross Abstract: Long-term memory lets LLM agents recall past interactions and remain consistent across sessions, but memory systems are hard to compare because they o

agentsarxiv-cs-ai

Applications

Taipan: A Query-free Transfer-based Multiple Sensitive Attribute Inference Attack Solely from Auxiliary Graphs

arXiv:2602.06700v2 Announce Type: replace-cross Abstract: Graph-structured data underpin a wide spectrum of modern applications, yet their multiple sensitive attributes are not isolated but deeply cou

applicationsarxiv-cs-lg

Talk2Agent: Benchmarking Voice Interfaces for Text Agents

arXiv:2609.38867v1 Announce Type: new Abstract: Large language model (LLM) computer-use agents are typically evaluated with clean written instructions, despite speech being an increasingly popular int

Local Ai

Template-Search Domain Adaptation via Multi-Stage Feature Alignment for Cross-Modal Object Tracking

arXiv:2609.38637v1 Announce Type: cross Abstract: Visual object tracking typically assumes that the initial template and subsequent search frames share the same sensing modality. In practice, sensor a

local-aiarxiv-cs-ai

Text-to-3D Policy: Fine-Grained Language-Behavior Alignment for Unseen Specification Generalization

arXiv:2609.39599v1 Announce Type: cross Abstract: 3D visuomotor policies provide a strong foundation for spatially precise manipulation, yet current text-to-3D policies struggle to follow unseen fine-

TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning

arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing meth

ThinkV2V: Unleashing the Reasoning Capability of MLLMs for Instruction-Guided Video Editing

arXiv:2609.38541v1 Announce Type: new Abstract: Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic

Toward Real-Time VLAs: Stage-Aware Two-Step Flow Denoising and System-Level Evaluation

arXiv:2609.39822v1 Announce Type: new Abstract: Vision-language-action (VLA) models face a timing gap between low-rate inference and high-rate robot execution. We characterize this gap through end-to-

researcharxiv-cs-ro

Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach

arXiv:2609.39397v1 Announce Type: cross Abstract: We study data-driven multi-period lost-sales inventory control under censored demand, where a stockout reveals only that demand exceeded the stocking

safetyarxiv-cs-lg

TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

arXiv:2609.32923v2 Announce Type: replace Abstract: Wireless digital twins (DTs) rely on 3D environment models to predict radio propagation and support wireless-network decisions, yet these models are

TrackFish3D: Self-Supervised 3D Tracking of Schooling Fish from Multi-view Videos

model-releasesarxiv-cs-cv

arXiv:2609.38347v1 Announce Type: new Abstract: Quantifying collective fish behavior requires accurate trajectories, yet multi-view 3D tracking remains challenging due to frequent occlusions, visually

TrafficSignBench: Rule-Centric Closed-Loop Evaluation of Traffic-Sign Compliance in Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.38463v1 Announce Type: cross Abstract: Autonomous driving planners are typically evaluated using aggregate metrics such as driving score, destination rate, and collision rate, which do not

Tutorials

TripleFlow: Training-Free Video Object Removal by Bridging Residual Editing and Native Generation

arXiv:2609.39157v1 Announce Type: new Abstract: Video object removal presents a uniquely difficult editing challenge. Because a removal prompt specifies only what to erase rather than what to generate

tutorialsarxiv-cs-cv

Trustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail

arXiv:2609.39086v1 Announce Type: cross Abstract: Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state. Recent work shows that LLMs can generate

Agents

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

agentsarxiv-cs-ai

TutlAit v1: a crowdsourced Moroccan Tamazight speech dataset with Arabic transcriptions and regional accent labels

arXiv:2609.38219v1 Announce Type: new Abstract: Tamazight (Amazigh) is, together with Arabic, one of the two official languages of Morocco, yet it remains severely under-resourced for speech technolog

researcharxiv-cs-cl

Two-Step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real

arXiv:2512.15774v5 Announce Type: replace Abstract: The absence of large-scale masked face datasets challenges masked face detection and recognition. We propose a two-step generative data augmentation

UGOD: Uncertainty-Guided Opacity and Dropout for Sparse-View 3D Gaussian Splatting

arXiv:2609.39089v1 Announce Type: new Abstract: Sparse-view 3D Gaussian Splatting is prone to overfitting because limited observations leave many Gaussian primitives weakly constrained, yet their cont

Understanding as No-Arbitrage: Bounded Dutch Books as a Definition and Training Objective for Language Models

arXiv:2609.39341v1 Announce Type: new Abstract: Does a language model merely predict tokens, or does it understand what it says? We make this question measurable by defining 'understanding' through th

UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement

arXiv:2609.38721v1 Announce Type: new Abstract: Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedbac

Unlearnable, or Unmeasured? On the Reliability of Difficulty Labels in RLVR

arXiv:2609.40115v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become an important approach for improving reasoning during post-training. Recent work suggest

Validity-Preserving Hierarchical RL for Joint Routing and Switch Placement in EDA

arXiv:2609.39749v1 Announce Type: new Abstract: Routing and switch placement are fundamental combinatorial optimization problems in chip design, requiring the joint optimization of routing topology an

researcharxiv-cs-lg