All entries

FinsSim: A Reality-Aligned Integrated Simulation Platform for Underwater Robot Learning

arXiv:2609.23943v1 Announce Type: new Abstract: Underwater robot learning relies on simulators that integrate high-fidelity hydrodynamics, convenient learning interfaces, and a credible transition to

researcharxiv-cs-ro

Content type

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Industry

Firecrawl, which provides web scraping tools for AI agents, raised a $75M Series B led by Smash Capital (Maria Deutscher/SiliconANGLE)

DGX agent

Maria Deutscher / SiliconANGLE: Firecrawl, which provides web scraping tools for AI agents, raised a 75M Series B led by Smash Capital — Firecrawl Inc., a provider of web scraping tools for artificial

industrytechmeme

22 Sept 2026

Tutorials

FIRM-WM: State-factorized factual-interventional recurrent modeling for reward-free visual planning

arXiv:2609.22816v1 Announce Type: new Abstract: Reward-free latent world models can learn from offline videos and solve new image--goal tasks by optimizing actions through predicted latent futures. Th

tutorialsarxiv-cs-lg

Industry

Fitch gives Tesla its first-ever BBB investment-grade credit rating. Fitch highlighted Tesla’s EV leadership, strong profitability, $43.5B i…

Fitch gives Tesla its first-ever BBB investment-grade credit rating. Fitch highlighted Tesla’s EV leadership, strong profitability, $43.5B in cash and investments, and “unmatched” vertical integration

industryelon-musk--x

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

Hardware

FlashBoB: I/O-Efficient Exact Backward-over-Backward for Softmax Attention

arXiv:2609.24089v1 Announce Type: new Abstract: Transformer models built on the attention mechanism have become a central building block in modern deep learning, yet softmax attention remains a major

hardwarearxiv-cs-lg

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

FoldQuantVLA: Native Low-Bit Quantization of Vision-Language-Action Models via Consistent Folding

arXiv:2609.24433v1 Announce Type: new Abstract: Low-bit vision-language-action inference must reduce observation-to-action latency while preserving robot behavior. We present FoldQuantVLA, a post-trai

safetyarxiv-cs-ro

ForceRFT: Refining VLA Actions through Force-Guided Residual Reinforcement Learning

arXiv:2609.22840v1 Announce Type: new Abstract: Force-conditioned vision-language-action (VLA) policies can respond to contact, but when trained solely on demonstrations, their recovery behavior may b

agentsarxiv-cs-ro

Forecasting Intrathecal Tracer Enhancement from Pre-Contrast Brain MRI: Direct Regression versus Flow Matching

arXiv:2609.22377v1 Announce Type: cross Abstract: Intrathecal contrast-enhanced MRI tracks how a cerebrospinal-fluid tracer spreads through the brain, but requires repeated scans over 24--48,h. Foreca

Fork of FreeToken with DeepSeek-V4.1, vision and speculative decoding (2x3090 numbers inside)

model-releasesr-localllama

I've been running FreeToken on my 2x3090 box for a while and ended up maintaining a fork of it. Posting it in case it's useful to anyone else here. Quick context if you haven't used it: FreeToken is a

Fractal basin geometry and the limits to predictability and reproducibility in deep learning

model-releasesarxiv-cs-lg

arXiv:2510.05606v2 Announce Type: replace Abstract: Fundamental limits to predictability are central to our understanding of many physical and computational systems. In deep learning, training outcome

FRAMES: Failure Recovery And Monitoring of Embodied Skills for Humanoid Loco-Manipulation

arXiv:2609.22538v1 Announce Type: new Abstract: Large language model (LLM) planners can decompose natural-language instructions and select reusable robot skills, but choosing the correct skill does no

agentsarxiv-cs-ro

From Articles to Publishers: Aggregating Language Model Predictions for News Source Reliability Inference

arXiv:2609.24219v1 Announce Type: new Abstract: Traditionally, the reliability of news publishers is assessed by expert organisations that evaluate editorial practices, transparency and factual standa

From Concept Alignment to Causal Grounding: An Intervention Test of Chain-of-Thought Faithfulness

arXiv:2609.23065v1 Announce Type: new Abstract: Chain-of-thought (CoT) can sound plausible yet be unfaithful to the model's underlying reasoning. Most prior work probes CoT faithfulness through input-

Tutorials

From Content Generation to Learning Support: Pedagogy-Guided Generative Video Tutors for STEM Learning

arXiv:2609.24083v1 Announce Type: new Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than su

tutorialsarxiv-cs-cl

From Documented Strengths to Force Limits: Material-Informed Robotic Insertion for Construction Assembly

model-releasesarxiv-cs-ro

arXiv:2609.22609v1 Announce Type: new Abstract: Insertion is a fundamental operation in robotic construction assembly, where variations in material properties and assembly conditions make it difficult

From Latent Biomarkers to Clinical Rules: Embedding-Guided Rule Mining and Attribution-Based Translation for Interpretable Tabular Learning

arXiv:2609.22155v1 Announce Type: new Abstract: Clinical decision support tools are most useful when accurate predictions are accompanied by understandable explanations. Rule-based models provide tran

From Noise to Signal: When Outliers Seed New Topics

arXiv:2603.18358v2 Announce Type: replace Abstract: Outliers in dynamic topic modeling are typically treated as noise, yet we show that some can serve as early signals of emerging topics. We introduce

From Outliers to Topics in Language Models: Anticipating Trends in News Corpora

arXiv:2509.22030v2 Announce Type: replace Abstract: This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Us

From Regional to Global: Transfer Learning for Atmospheric Transport Emulators

arXiv:2609.23838v1 Announce Type: new Abstract: Greenhouse gas emissions estimates can be derived using inverse methods by combining atmospheric concentration observations with chemical transport mode

From Semantic Decisions to Feasible Trajectories: Self-Evolving LLM-Guided Optimal Control for Narrow-Space Parking

arXiv:2609.24631v1 Announce Type: new Abstract: Autonomous parking in nonconvex and narrow environments remains challenging. Although optimal-control methods can explicitly enforce vehicle dynamics an

agentsarxiv-cs-ro

From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification

arXiv:2609.23966v1 Announce Type: new Abstract: LLMs can generate fluent descriptions from tables, but their outputs may remain logically unsupported by the structured data. We introduce STAT-TO-TEXT,

From Trait Vectors to Circuits: Tracing Refusal and Sycophancy Through Language Models

arXiv:2609.22224v1 Announce Type: new Abstract: A direction in activation space that changes safety-relevant behavior when steered is not necessarily one the model uses to produce that behavior on its

From UNDRR Reports to Event Records: Schema-Constrained LLM Extraction of Georeferenced Disasters

model-releasesarxiv-cs-cl

arXiv:2609.23853v1 Announce Type: new Abstract: Disaster-risk-reduction archives describe hazard events in prose that databases such as EM-DAT (Delforge et al., 2025) cannot ingest directly. We presen

Functional Emotion Without Character: Large Language Models, Aristotelian Disposition, and the Limits of Behavioral Alignment

arXiv:2609.22362v1 Announce Type: new Abstract: Debates about whether artificial systems can feel are often forced between two unsatisfactory positions: behavioral equivalence is treated as sufficient

G-NAC: Graph Neural Automata Clustering via Emergent Domain Formation

model-releasesarxiv-cs-lg

arXiv:2609.24823v1 Announce Type: new Abstract: We introduce Graph Neural Automata Clustering (G-NAC), an unsupervised clustering method in which observations interact as cells on a fixed neighborhood

Hardware

G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulation

arXiv:2609.23566v1 Announce Type: new Abstract: 6D object pose estimation is fundamental to robotic manipulation and automation. Recent zero-shot methods have significantly improved generalization to

hardwarearxiv-cs-cv

GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World Generation

arXiv:2609.24981v1 Announce Type: new Abstract: We present a compact geometry-native latent space as a shared foundation for perception and generation. Visual generators can produce photorealistic fra

GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay

arXiv:2609.25001v1 Announce Type: new Abstract: Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, an

GameReplica: A Benchmark for Black-Box Visual Game Replication by Vision-Language Agents

arXiv:2609.22308v1 Announce Type: new Abstract: Coding-agent benchmarks usually evaluate implementation after the target behavior has been specified in text, code, or demonstrations. Existing research

GAPS: Generative Active Pseudo-view Selection for Sparse-View 3D Gaussian Splatting

arXiv:2609.23436v1 Announce Type: new Abstract: Novel view synthesis from sparse observations is severely under-constrained. Although 3D Gaussian Splatting (3DGS) enables real-time rendering, it produ

Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning

model-releasesarxiv-cs-cl

arXiv:2601.06787v2 Announce Type: replace Abstract: Large Language Models (LLMs) are known to contain significant redundancy, yet a systematic explanation for why certain components, particularly in h

Applications

GARO: Geometry-Aware Redundancy Optimization for Real-Time and High-Fidelity Dynamic Gaussian Splatting

arXiv:2609.23509v1 Announce Type: new Abstract: Novel view synthesis is a key task for dynamic scene reconstruction, where high rendering speed is essential for applications such as virtual reality. E

applicationsarxiv-cs-cv

Gaussian Process Decorrelation for Spatiotemporal Deep Learning-Based Snow Water Equivalent Prediction

arXiv:2609.22182v1 Announce Type: new Abstract: In the Western United States, snowmelt is essential to the agricultural industry in addition to being a key source of municipal drinking water. Conseque

safetyarxiv-cs-lg

GDN Tree-Scan: Served Tree Verification for Recurrent-Hybrid Language Models

arXiv:2609.23900v1 Announce Type: new Abstract: Tree speculative decoding verifies multiple candidate continuations in one target forward pass. For attention-only transformers, the verifier mainly nee

safetyarxiv-cs-lg

GeCCo -- a Generalist Contact-Conditioned Policy for Loco-Manipulation Skills on Legged Robots

arXiv:2509.17582v2 Announce Type: replace Abstract: Most modern approaches to quadruped locomotion focus on using Deep Reinforcement Learning (DRL) to learn policies from scratch, in an end-to-end man

safetyarxiv-cs-ro

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

arXiv:2609.22967v1 Announce Type: new Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compa

Generalizable Optimal Control with Transformers: One Policy Across Diverse Systems

model-releasesarxiv-cs-ro

arXiv:2603.14910v2 Announce Type: replace-cross Abstract: Classical optimal control designs a separate controller for each plant. Even for the Linear Quadratic Regulator (LQR), every new model must be

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

Genie One MCP: Give any AI Agent the Right Business Context

**Genie One MCP: Give any AI Agent the Right Business Context** The guide introduces Genie One MCP as a framework for embedding relevant business context in artificial intelligence agents, enabling th

agentsdatabricks

GenVoid: Uncertainty-Aware Learning of Subsurface Material Defects with an Experimentally Validated Physics-Informed Generative Model

arXiv:2609.23761v1 Announce Type: new Abstract: Internal voids are ubiquitous defects in manufactured structures, yet their characterization remains challenging because their geometry is hidden and ca

GeoBalance: Geometry-Aware Monitoring and Reconstruction with Asymmetric Optimization for Balanced Multimodal Learning

arXiv:2609.23533v1 Announce Type: new Abstract: Multimodal classifiers can converge to modality-dominant solutions in which one modality dominates the joint prediction, suppressing the learning of oth

Glass-Box Deep Learning for FDIA Detection in Nonlinear Automatic Generation Control: A Kolmogorov-Arnold Network Approach

model-releasesarxiv-cs-lg

arXiv:2509.05259v2 Announce Type: replace Abstract: Automatic Generation Control (AGC) plays a critical role in maintaining power balance across multi-area power systems. However, its complete relianc

Global Ranks Survive, Selected Heads Shift: BOS-Sink Topology under 4-bit Weight-Only Quantization

model-releasesarxiv-cs-cl

arXiv:2609.23585v1 Announce Type: cross Abstract: Sink-aware deployment may identify important first-token attention heads before a model is quantized, then reuse that map at the edge. We test when th

GLR-MM: Graph-Based Global-Local Reconstruction for Robust Multimodal Chest X-ray and EHR Representation Learning under Missing Modalities

arXiv:2609.23876v1 Announce Type: new Abstract: Clinical multimodal models must often predict before all chest X-ray (CXR) and electronic health record (EHR) inputs are available. Existing approaches

GNN-based Path-aware multi-view Circuit Learning for Technology Mapping

arXiv:2601.14286v2 Announce Type: replace-cross Abstract: Traditional technology mapping suffers from systemic inaccuracies in delay estimation due to its reliance on abstract, technology-agnostic del