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FinLifeBench: Exhaustive Life-Event History and Financial-State Reconstruction from Longitudinal Banking Dialogue

arXiv:2609.01198v1 Announce Type: new Abstract: Repeated banking interactions require assistants to maintain complete, current, and traceable customer records as life changes emerge incidentally in ro

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Model Releases

First local-LLM tuning attempt: Qwen3.8-27B true Q4_K_M at 13.2 tok/s near 50-61K context on RTX 5080 16GB

DGX agent

This was my first serious attempt at tuning a local LLM. I started because Qwen3.8-27B IQ3 was fast on my RTX 5080 but the coding quality disappointed me, and the Q4 profiles I tried in LM Studio were

model-releasesr-localllama

2 Sept 2026

Tutorials

Fizgig 5.2 - combining two Minimax training methods beats either alone

tutorialsr-stablediffusion

Two of the ways that exist (im sure there are more) to train a LoRA on H3 well are on two different trainers. Fizgig's is Optimised Likeness Learning: I've found the stable core of H3's identity lives

FLaG: Frequency-Domain Latent-attention Gated Pooling for Token Aggregation

arXiv:2609.00831v1 Announce Type: new Abstract: Token aggregation converts token-level representations into fixed-dimensional sample representations, but most pooling methods operate only in the origi

Flawed in Nature, Perfect through Evolution

arXiv:2609.00129v1 Announce Type: cross Abstract: The performance of artificial intelligence (AI) and machine learning (ML) models degrades when the problem they were trained on drifts. This is a near

agentsarxiv-cs-ai

Fleets Need a Context Plane: Rethinking Cooperative Perception for Autonomous Drones

model-releasesarxiv-cs-ro

arXiv:2609.00659v1 Announce Type: new Abstract: Cooperative perception allows a drone fleet to combine observations from multiple viewpoints. However, existing systems typically fix their feature-shar

FlexP-SFT: A Flexible Aggregation-Free Framework for On-Device Personalized Split Federated Fine-Tuning of LLMs

arXiv:2508.10349v2 Announce Type: replace-cross Abstract: To fine-tune large language models (LLMs) over private data, federated learning (FL) has emerged as a promising paradigm. However, the prohibi

FloydNet: A Learning Paradigm for Global Relational Reasoning

arXiv:2601.19094v3 Announce Type: replace-cross Abstract: Learning algorithmic computation often requires explicit relational intermediate states, yet many graph processors maintain their primary stat

FoldingAgent: Inferring Parametric Origami Procedures from Demonstration Videos

arXiv:2609.00377v1 Announce Type: cross Abstract: We present FoldingAgent, an agentic framework for inferring explicit parametric folding programs directly from origami demonstration videos. Our frame

Tutorials

Forbid Your Attention: Fooling Multimodal Large Language Models by Selectively Removing Intrinsic Focus in Spectral Domain

arXiv:2609.00788v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have extended the capability of large language models (LLMs) to process more contextual multimodal information,

tutorialsarxiv-cs-cv

Foundation models for electricity price forecasting and battery arbitrage: Can they replace market-specific forecasting models?

arXiv:2609.00089v1 Announce Type: new Abstract: Foundation models promise accurate forecasts with little or no task-specific training, but whether they can replace models designed specifically for ele

Fractal dimension predicts quantum kernel collapse in angle-encoded data

arXiv:2609.00475v1 Announce Type: cross Abstract: Angle-encoded quantum kernels on tabular data collapse when the feature map is wider than the intrinsic dimension of the data. We propose the correlat

FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study

arXiv:2609.00875v1 Announce Type: new Abstract: Satellite mega-constellations are emerging as large-scale sensing, communication, and computation fabrics, yet their learning architectures remain large

Freeze, Diffuse, Decode: Geometry-Aware Adaptation of Pretrained Transformer Embeddings for Antimicrobial Peptide Design

arXiv:2511.23120v2 Announce Type: replace Abstract: Pretrained transformers provide rich, general-purpose embeddings, which are transferred to downstream tasks. However, current transfer strategies: f

From Base Rollouts to RL Reasoning: A Budgeted Search Perspective

model-releasesarxiv-cs-cl

arXiv:2609.01274v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves language-model reasoning, but how these gains relate to inference-time decoding and searc

From code to diagrams: Agentic architecture documentation with Amazon Bedrock AgentCore

Learn how a global interdealer broker built an automated architecture documentation pipeline on Amazon Bedrock AgentCore that analyzes .NET code bases, generates architecture diagrams, and maintains s

agentsaws-ml-blog

From Confusion to Clarity: Confusion-Aware Retrieval and Knowledge Injection for Text Classification

arXiv:2609.01564v1 Announce Type: cross Abstract: Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific

From Detection to Refusal: Safer LLMs via Circuit-Guided Weight Scaling

arXiv:2609.00051v1 Announce Type: cross Abstract: Despite extensive alignment efforts, Large Language Models (LLMs) remain vulnerable to generating unsafe content under adversarial prompting, yet the

Applications

From Language to Behavior: Scaling Sequence Transformers for Industrial Recommendation Ranking with Rec-Native Designs

arXiv:2609.01240v1 Announce Type: cross Abstract: Scaling Transformers has driven large gains in language modeling, but transplanting this to behavior-sequence modeling in production ranking is challe

applicationsarxiv-cs-ai

From Legible to Inscrutable Trajectories: (Il)legible Motion Planning Accounting for Multiple Observers

arXiv:2602.09227v2 Announce Type: replace Abstract: In cooperative environments, such as in factories or assistive scenarios, it is important for a robot to communicate its intentions to observers, wh

agentsarxiv-cs-ro

Applications

From metal to model: Private cloud gets an assembly line for production AI

Enterprises moving artificial intelligence from pilot projects into production are discovering that the hard part is no longer the model. It’s the infrastructure beneath it. Cost, tokenomics, data pri

applicationssiliconangle

Hardware

From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix

arXiv:2609.01572v1 Announce Type: new Abstract: Data-residency constraints force enterprises to self-host LLMs, but continuous adoption of newer models without decommissioning their predecessors expan

hardwarearxiv-cs-cl

From Rollouts to Recipes: Self-Contained Post-Training for LLMs

arXiv:2609.01422v1 Announce Type: new Abstract: Post-training large language models usually applies a single training recipe to all samples, even though the model's own rollouts reveal different sampl

safetyarxiv-cs-cl

From Saliency to Discriminability: Rank-Preserving Visual Token Pruning for VLM Rerankers

arXiv:2609.00667v1 Announce Type: cross Abstract: Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning ess

researcharxiv-cs-cv

From Terminology to Diagrams: Visual-Instruction Generation for Scientific Diagram Understanding

arXiv:2609.00948v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated strong performance in visual question answering with natural images. However, they continue to struggl

From Tool Use to Technological Agency: LoopCAT as a Local-First, Open-Source Tool for Translation Technology Education

model-releasesarxiv-cs-cl

arXiv:2609.00344v1 Announce Type: new Abstract: Translation students need to learn both how to use translation technologies and how to judge the choices those technologies make available. This article

From Truncation to Commitment: Persistent Context in Uniform Discrete Diffusion

arXiv:2609.01043v1 Announce Type: cross Abstract: Uniform-state discrete diffusion models update all tokens in parallel while keeping every position revisable. Even when the commonly used top-p rule l

Industry

Frontier AI research moves into cyber defense as attackers gain speed

Frontier artificial intelligence research is moving into security operations, and the arrival of a cyber superintelligence lab at one of the industry’s largest platform companies marks how far that sh

industrysiliconangle

Frozen Cores Need Task Signal: Fisher-Whitened Cross-Covariance for Low-Resource LLM Adaptation

arXiv:2609.00762v1 Announce Type: new Abstract: Parameter-efficient fine-tuning is usually framed as a question of how many parameters to update. Under a severe trainable-state budget, however, where

Local Ai

FTU-Seek: Foundation Model-Guided Hard-Negative Learning for Sparse Functional Tissue Unit Segmentation

arXiv:2609.00704v1 Announce Type: new Abstract: Functional tissue units (FTUs), including tertiary lymphoid structures (TLSs), blood vessels, and glands, encode localized immune, vascular, and epithel

local-aiarxiv-cs-cv

Further evidence for @GaryMarcus 's worries about the security competence of the people running AI. Vibe coding without then checking securi…

Further evidence for @GaryMarcus 's worries about the security competence of the people running AI. Vibe coding without then checking security is not impressive 🚨 Attackers stole a METR API key and us

agentsgary-marcus--x

Gaussian Core LoRA: Distribution-Aware Dynamic Adaptation for Broad Concept Erasure

model-releasesarxiv-cs-cv

arXiv:2609.01433v1 Announce Type: new Abstract: Concept erasure aims to suppress unsafe, privacy-sensitive, or undesirable generations in text-to-image diffusion models while preserving benign semanti

GazeRefine: Expert Gaze as a Test-Time Prompt for Training-Free Medical Image Segmentation

arXiv:2609.01310v1 Announce Type: cross Abstract: Medical image segmentation remains difficult to scale because high-performing methods typically rely on dense expert annotations and task-specific tra

Generalization Bounds for Markov Algorithms through Entropy Flow Computations

arXiv:2502.07584v3 Announce Type: replace-cross Abstract: Many learning algorithms can be represented as Markov processes, and understanding their generalization error is a central topic in learning t

Generative artificial intelligence for reliable mechanistic reasoning for corrosion

arXiv:2609.00099v1 Announce Type: new Abstract: Corrosion accounts for approximately 4% of global GDP, and reliable prediction is essential for timely mitigation. Machine learning effectively predicts

Generativism: Toward a Learning Theory for the Age of Generative Artificial Intelligence

arXiv:2606.12441v2 Announce Type: replace-cross Abstract: The four dominant learning theories of behaviorism, cognitivism, constructivism, and connectivism show significant conceptual limitations as g

Applications

GENIE: Watermarking Graph Neural Networks for Link Prediction

arXiv:2406.04805v4 Announce Type: replace-cross Abstract: The rapid adoption, usefulness, and resource-intensive training of Graph Neural Network (GNN) models have made them an invaluable intellectual

applicationsarxiv-cs-lg

GenONet: A Generative operator Network for High-Resolution Precipitation Nowcasting

arXiv:2609.00544v1 Announce Type: new Abstract: High-resolution precipitation nowcasting is critical for reducing the impacts of severe weather but remains difficult because of rapid storm evolution.

GenScale: A Benchmark for Relative Object Scale in Image Generation and Editing

model-releasesarxiv-cs-cv

arXiv:2609.00525v1 Announce Type: new Abstract: Modern image generation and editing systems can produce photorealistic, prompt-aligned images, but still often render familiar objects at implausible re

GeoGR^2:Zero-Shot Geospatial Inference via Geostatistically-Guided Iterative Refinement with LLMs

arXiv:2508.04080v2 Announce Type: replace Abstract: Standard large language model prompting treats geospatial inference as independent, instance-wise prediction, ignoring the fundamental spatial depen

Geometric analysis of generic 3R robots, and necessary and sufficient conditions for a class of orthogonal robots to have four IKS

arXiv:2609.00316v1 Announce Type: new Abstract: The kinematic analysis of a generic 3R robot has been investigated with multiple approaches in the past. The algebraic approaches have established concr

researcharxiv-cs-ro

Geometry-aware Latent Autoregressive Generative Model for PDEs in Complex Domains

arXiv:2609.00297v1 Announce Type: cross Abstract: Solving multiphysics partial differential equations (PDEs) remains a major challenge in scientific computing, especially for highly complex mum-scale

Local Ai

GeoPAR: Large-Scale Multi-Agent Combinatorial Optimization with Geometry-Guided Parallel Autoregressive Learning

arXiv:2609.00577v1 Announce Type: cross Abstract: Multi-agent combinatorial optimization problems are notoriously challenging due to their NP-hard nature. Recent parallel autoregressive neural solvers

local-aiarxiv-cs-ai

Getting started with Mantis, our open-source bug finding-and-fixing harness

AI models have clearly proven their ability to discover and exploit vulnerabilities without much, if any, human assistance. To help defenders gain the advantage with AI, we built the Mantis harness to

agentsgoogle-cloud-ai

GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions

arXiv:2609.01491v1 Announce Type: cross Abstract: The growing rate at which LLM agents interact with one another raises key questions about language evolution in multi-LLM-agent settings, with implica

Good Memory Has ECC: Evaluating the Memory of Vision-Language Models Beyond Accuracy

arXiv:2609.00103v1 Announce Type: cross Abstract: Memory is widely viewed as an important unsolved problem for LLMs and VLMs, and current benchmarks typically evaluate it by testing accuracy over long

Google is sending MrBeast into the wilderness, armed with AI

model-releasesthe-verge-ai

MrBeast will feature Gemini, Google Health, and the Fitbit Air in upcoming videos as part of a multi-year partnership with Google. The deal will kick off with a video featuring Jimmy 'MrBeast' Donalds

Google launches Gemini 3.8 Flash Cyber for partners in its new Fairwind Program and says Gemini 3.8 Flash beats Claude Opus 5 and GPT-5.6 Sol on some benchmarks (Google)

Google: Google launches Gemini 3.8 Flash Cyber for partners in its new Fairwind Program and says Gemini 3.8 Flash beats Claude Opus 5 and GPT-5.6 Sol on some benchmarks — Our newest Gemini models deli

model-releasestechmeme