All entries

ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize

arXiv:2609.04197v1 Announce Type: cross Abstract: Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3imes longer y

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Research

Establishing a Dynamic Multimodal HRI Dataset for Engagement Analysis with a Humanoid Robot

DGX agent

arXiv:2609.03255v1 Announce Type: new Abstract: This paper presents an experimental design for constructing a multimodal dataset to analyze user engagement in human-robot interaction (HRI). Prior stud

researcharxiv-cs-ro

4 Sept 2026

Evaluating Criterion-Conditioned Behaviour of Large Language Models in Content Moderation

arXiv:2609.03814v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance on standard content moderation benchmarks. However, these benchmarks often aggregate multipl

Evaluating GNNs for Success Prediction in Artist Collaboration Networks

arXiv:2609.02920v1 Announce Type: cross Abstract: As the music industry becomes an increasingly collaborative effort, understanding the underlying structures of the artist network has become a focal p

Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts

arXiv:2609.02996v1 Announce Type: cross Abstract: Graph neural networks (GNNs) are a class of neural networks suitable for learning on graph-structured data. Their application to spatial data is a nat

Evaluating Large Language Models on Urdu Idioms

arXiv:2510.17460v2 Announce Type: replace Abstract: Idioms remain a persistent challenge in natural language processing due to their figurative and culturally grounded meanings, which distinguish them

Even Qwen3.8 followed the instruction inside my translation data, and Gemma 4 beat the translation specialists I tested

model-releasesr-localllama

A month ago I posted about Gemma sometimes solving the reasoning problems inside my translation data instead of translating them. A few people suggested two very fixes, which is to use a proper transl

Everpure sees AI infrastructure strategy move beyond virtual machines

AI infrastructure strategy is expanding beyond compute and storage specifications as artificial intelligence reshapes who manages enterprise applications and data. Infrastructure teams are increasingl

applicationssiliconangle

Tools

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published rese…

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind thos

toolsperplexity--x

Evolving Excellence: Automated Optimization of LLM-based Agents

arXiv:2512.09108v2 Announce Type: replace-cross Abstract: Agentic AI systems built on large language models (LLMs) offer significant potential for automating complex workflows, from software developme

Ex-Omni: Enabling 3D Facial Animation Generation for Omni-modal Large Language Models

arXiv:2602.07106v3 Announce Type: replace-cross Abstract: Omni-modal large language models (OLLMs) aim to unify multimodal understanding and generation, yet extending them to jointly produce speech an

Exemplar: Classical Priors Complement Frozen Features for Few-Shot Microscopy Segmentation at Native Resolution

arXiv:2609.03080v1 Announce Type: new Abstract: Segmenting a new biomedical dataset usually means a domain-specific model trained on substantial annotation, or a foundation model steered at inference

Experian expands into AI agents with ServiceNow partnership

Having launched an artificial intelligence-based virtual assistant in the spring, Experian plc is driving AI deeper into its operations with a commercial agent-based platform designed to bring its ris

agentssiliconangle

Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus Images

arXiv:2405.07338v2 Announce Type: replace-cross Abstract: Early detection of vision-threatening conditions such as diabetic retinopathy, glaucoma, and age-related macular degeneration depends on retin

Exploring the Potential of Contrastive Language-Image Pre-training for Multi-Source Remote Sensing Data

arXiv:2609.03391v1 Announce Type: cross Abstract: Contrastive language-image learning (CLIP) has become a key paradigm for remote sensing vision-language understanding. However, existing remote sensin

Extracting Forgotten Prompts from Targeted Unlearned Models

arXiv:2609.03662v1 Announce Type: new Abstract: Recent unlearning methods (e.g. NPO, DPO, LUNAR) make use of refusal alignment to suppress forgotten data. However, it has been shown that refusal respo

safetyarxiv-cs-lg

F4Splat: Feed-Forward Predictive Densification for Feed-Forward 3D Gaussian Splatting

arXiv:2603.21304v3 Announce Type: replace Abstract: Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-G

FailBench: How Reliable are VLMs at Judging Robot Task Success?

arXiv:2609.03611v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used to evaluate robot manipulation outcomes, but existing benchmarks offer limited evidence of cross-d

Feasible but Not Safe: Constraint Violations and Report-Channel Attacks in Learned Cell-Free ISAC Association

arXiv:2609.03147v1 Announce Type: cross Abstract: Learning-based schedulers have been proposed to provide real-time user, target, and access point (AP) association in distributed cell-free integrated

Feature Reconfiguration With Visual Prior for Medical Lesion Segmentation

arXiv:2609.03535v1 Announce Type: new Abstract: Lesion segmentation in medical images plays a critical role in clinical diagnosis and treatment planning. Despite significant advances, lesion segmentat

Federated Causal Discovery via Regression-Directed Cumulants

arXiv:2609.03705v1 Announce Type: new Abstract: In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Marko

FedPS: Federated Preprocessing for structured data via aggregated Statistics

arXiv:2602.10870v2 Announce Type: replace-cross Abstract: Federated Learning (FL) enables multiple parties to collaboratively train machine learning models without sharing raw data. However, before tr

Industry

Filing: AI training data startup Micro1 offers to pay 12.5M for Spirit Airlines' data; the offer faces hurdles as Spirit already has a 10M deal with Google (Jonathan Randles/Bloomberg)

Jonathan Randles / Bloomberg: Filing: AI training data startup Micro1 offers to pay 12.5M for Spirit Airlines' data; the offer faces hurdles as Spirit already has a 10M deal with Google — An artificia

industrytechmeme

Fill My Mirror: Geometry-Constrained Mirror Inpainting

arXiv:2609.03740v1 Announce Type: new Abstract: Mirrors are common in real-world images, yet producing geometrically consistent reflections with generative models remains challenging. Unlike most obje

applicationsarxiv-cs-cv

FiMI Banking: A Sovereign Model for Indian Retail Banking

arXiv:2609.03960v1 Announce Type: new Abstract: Banks need conversational systems that can answer product questions, assist customers with account-related requests, and operate safely within strict op

agentsarxiv-cs-ai

Finite-Time Convergence of Single-Trajectory Chi-Square Robust Q-Learning With Linear Function Approximation

arXiv:2510.01721v4 Announce Type: replace Abstract: Distributionally robust reinforcement learning seeks policies that remain effective when the deployment environment differs from the one that genera

Fixed Suffix Dependency Ratio: Quantifying the Dual-Track Mechanism of Gender Assignment in Latvian Loanwords

arXiv:2609.03930v1 Announce Type: new Abstract: Existing research has repeatedly observed the tendency for English loanwords to cluster in the masculine gender across different recipient languages, ye

researcharxiv-cs-cl

FlashRender: Few-Step Generative Rendering via Camera-Controlled Video MeanFlow

arXiv:2609.03563v1 Announce Type: new Abstract: We present FlashRender, a few-step generative rendering framework that retakes a source video along a target camera trajectory in seconds. We identify s

safetyarxiv-cs-cv

FlexMap: Robust HD Map Construction under Flexible Camera Configurations

arXiv:2601.22376v2 Announce Type: replace Abstract: High-definition (HD) maps provide essential semantic information about road structures for autonomous driving, but existing HD map construction meth

agentsarxiv-cs-cv

Hardware

Flip, Don't Shuffle: Watermarking LLMs at the Speed of Inference

arXiv:2609.03844v1 Announce Type: cross Abstract: We introduce Stateless Bernoulli Watermarking (SBW), a new statistical watermark for Large Language Models that determines green list membership throu

hardwarearxiv-cs-cl

FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

arXiv:2609.03241v1 Announce Type: cross Abstract: A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse superv

FLY-EVAL++: An Evidence-Driven Evaluation Protocol for Safety-Constrained Flight Prediction with Large Language Models

arXiv:2609.04021v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in safety-critical, physics-governed environments requires more than accuracy-based metrics, because predictions

Following a Unique Path: A Fast Certifier Applied to Outlier-Robust Pose Registration

arXiv:2609.03222v1 Announce Type: new Abstract: Certifiable methods have arisen as a means to guarantee global optimality of solutions to non-convex problems using convex semidefinite programming (SDP

applicationsarxiv-cs-ro

For how much I use AI and automation, you'd THINK I run 100% of my business through Codex or Claude Code or Slack. But I still use native ap…

model-releasesallie-k--miller--x

For how much I use AI and automation, you'd THINK I run 100% of my business through Codex or Claude Code or Slack. But I still use native apps. I talk to several people who brag that 'they don't even

for the first time in a year, @OpenAI's model launch has been better received than a Claude launch. https://www.latent.space/p/ainews-gpt-6-…

for the first time in a year, @OpenAI's model launch has been better received than a Claude launch. https://www.latent.space/p/ainews-gpt-6-astra-openais-biggest this is a huge upset that we had previ

model-releasesswyx--x

FoRIS: Progressive Foreground Refinement for Training-Free In-Context Segmentation

arXiv:2609.03384v1 Announce Type: new Abstract: In-Context Segmentation (ICS) aims to precisely segment arbitrary semantic concepts, such as objects or parts, given one or a few annotated visual exemp

Formation Matrix and Energy-based Control of Multi-Agent Systems

arXiv:2609.04158v1 Announce Type: cross Abstract: This paper presents an energy-based controller for a multiagent robotic system designed to achieve and maintain a specific formation while moving on a

agentsarxiv-cs-ro

FPCO-Dialog: A Multi-Turn False-Premise Benchmark for Correction and Cooperation in Vision-Language Models

arXiv:2609.03331v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in multi-turn settings where users may describe visual content with incorrect assumptions. Yet e

FrameBench:A Language Understanding Benchmark Based on Frame Semantics

arXiv:2609.03370v1 Announce Type: new Abstract: In frame semantics, sentence comprehension is assumed to proceed by relating lexical meaning to background knowledge called semantic frames, thereby ena

Free Pause Tokens

arXiv:2609.03807v1 Announce Type: cross Abstract: A free pause token gives a language model extra compute to form each next-token prediction (as a pause, or thinking, token does) but carries that comp

Fresh Memory, Stale Plans: Dependency-Scoped Validation for Distributed LLM-Agent Memory

arXiv:2609.03340v1 Announce Type: new Abstract: Distributed LLM-agent teams can read the latest shared facts and still act on an obsolete plan. A planner may derive an action from requirement r_3, ano

FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions

arXiv:2609.02948v1 Announce Type: cross Abstract: Predicting the thermodynamic properties of an alloy requires sampling its configurations across many chemical conditions and recovering free energies

From Deceptive Outputs to Deceptive Mechanisms: A Causal Framework for Language-Model Deception Research

arXiv:2609.04166v1 Announce Type: new Abstract: Research and news coverage of language-model deception increasingly attributes human-like mental-state concepts to language models. Such claims can blur

From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

arXiv:2609.02984v1 Announce Type: new Abstract: The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundament

applicationsarxiv-cs-lg

Tutorials

From Nowcasting to Forecasting: Adapting a Reanalysis-Trained

arXiv:2609.03763v1 Announce Type: new Abstract: Accurate cloud-cover forecasts are important for temperature prediction, radiation forecasting, and solar-power operations. Short-range forecasting meth

tutorialsarxiv-cs-lg

From Ordered Bernoulli Levels to Critical-Line Geometry: Integer Quantization, Bernoulli Residual Phase, and Prime-Power Spectra

arXiv:2609.03801v1 Announce Type: new Abstract: We study the ordered Bernoulli-word kernel f(p,n,k)=p^k(1-p)^(n-k) and the geometry generated by its inverse-integer level sets. The binary level 2^(-n)

From Prior-Guided Heuristics to Deployable Agents: Accelerating Demonstration-Driven Reinforcement Learning for Deadline-Constrained Network Control

arXiv:2609.03590v1 Announce Type: cross Abstract: Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is essential for NextG interactive applications, yet providing str

From Zero to Hero: An Open LLM Ecosystem for Armenian

arXiv:2609.03350v1 Announce Type: cross Abstract: Pretraining data for Armenian, a morphologically rich and low-resource language, is scarce, and no open Armenian LLM has been released with the data a