Search: “framework”

Semantic Watermarking for Malicious Image Manipulation Detection

arXiv:2609.39623v1 Announce Type: new Abstract: The proliferation of high-fidelity generative editing models has made it possible to inject violent or sexual content into otherwise ordinary images whi

researcharxiv-cs-cv

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Sequential Bayesian Evaluation of Large Language Model Behavior

DGX agent

arXiv:2511.10661v2 Announce Type: replace Abstract: It is increasingly important to evaluate the characteristics of systems based on large language models (LLMs). Evaluations in this context often rel

model-releasesarxiv-cs-cl

1 Oct 2026

SETA: Scaling Environments for Terminal Agents

arXiv:2607.10891v2 Announce Type: replace Abstract: Large language models (LLMs) are rapidly shifting toward agents that solve tasks through diverse interfaces, including web and graphical user interf

Shifting Mechanisms: How Positional Encoding Choice Shapes In-Context Retrieval

arXiv:2609.38530v1 Announce Type: new Abstract: Language models increasingly use architectures that vary attention span and positional encoding across layers, such as applying RoPE with sliding-window

researcharxiv-cs-cl

Spike-driven Vision-Language-Action Model

arXiv:2609.39514v1 Announce Type: new Abstract: Vision-language-action (VLA) models bridge multimodal understanding and robotic control, advancing the dominant paradigm for embodied intelligence. Howe

researcharxiv-cs-cl

STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction

arXiv:2609.40245v1 Announce Type: cross Abstract: Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-L

Local Ai

Strong Multilingual Privacy Tagging at Encoder Speed

arXiv:2609.38630v1 Announce Type: new Abstract: Privacy redaction must remove personal information while preserving relationships expressed in text. We develop a multilingual named-entity tagger with

local-aiarxiv-cs-cl

Structural Limits of the Information-Theoretic Uncertainty Decomposition

arXiv:2609.39591v1 Announce Type: new Abstract: Uncertainty estimation in machine learning typically decomposes uncertainty into aleatoric uncertainty (AU) and epistemic uncertainty (EU) using the sta

researcharxiv-cs-cv

The Nixtlaverse: An Open-Source Ecosystem for Forecasting

arXiv:2609.39741v1 Announce Type: new Abstract: Large forecasting applications often combine statistical, machine-learning, and neural models. These families solve the same problem but differ in fitte

Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification

arXiv:2609.39429v1 Announce Type: cross Abstract: Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis. In this work, we evaluate UQ in a multi

Local Ai

VirusCascade: Hijacking Collaborative Reflection in LLM-Powered Recommender Agents

arXiv:2609.38270v1 Announce Type: cross Abstract: Advancing beyond traditional static scoring models, LLM-powered agentic recommender systems (LLM-ARS) instantiate users and items as autonomous agents

local-aiarxiv-cs-lg

Visualizing Distribution Coverage in Generative Diffusion Models

arXiv:2609.38853v1 Announce Type: new Abstract: Diffusion distillation is widely adopted to accelerate sampling, and the resulting few-step models are broadly believed to match or even surpass their m

When Scientific Contradictions Are Lost in Translation

arXiv:2609.38621v1 Announce Type: new Abstract: Two scientific findings can disagree without contradicting each other. Determining whether they conflict requires knowing whether they describe comparab

Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

arXiv:2609.38274v1 Announce Type: new Abstract: The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive

researcharxiv-cs-cl

Whose Voice Survives the Summary? A Voice-Retention Audit of LLM Employee Listening

arXiv:2609.38818v1 Announce Type: new Abstract: Organizations increasingly route employee feedback to leaders through large language model (LLM) summaries, an unaudited layer that silences already-spo

Agents

You're Hired: Strategic Model Selection for LLM Collaboration

arXiv:2609.38816v1 Announce Type: new Abstract: While multi-agent and model collaboration algorithms gain traction to combine the strengths of diverse Large Language Models (LLMs), existing systems re

agentsarxiv-cs-cl

A Mesoscopic View of Transformer Weights Through Row and Column Scale Fields

arXiv:2609.35852v1 Announce Type: new Abstract: Pooled statistics of Transformer weights obscure how magnitude is distributed across functional channels, while individual weights are too numerous to c

A robust single-sensing-element tactile sensor for concurrent pressure and tackiness detection with real-time signal decoupling capability

arXiv:2609.36558v1 Announce Type: new Abstract: Integrating tackiness sensation into the artificial skin of humanoid robots significantly enhances their cognitive and operational capabilities. However

researcharxiv-cs-ro

Tutorials

Abductive World Modeling via Causal Representation Learning

arXiv:2609.36985v1 Announce Type: cross Abstract: The central challenge of world modeling is to learn representations that capture how the world evolves. However, existing world models predominantly r

tutorialsarxiv-cs-ai

Adam under Generalized Smoothness with Second-Moment-Type Stochastic Gradients

arXiv:2609.37787v1 Announce Type: new Abstract: Adam is widely observed to remain stable even when the objective deviates significantly from global smoothness. Under the generalized smoothness framewo

AdaptArena: Evaluating Test-Time Personalization of Web Agents

arXiv:2609.36488v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings w

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations

arXiv:2609.36915v1 Announce Type: cross Abstract: Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities fo

ARCagent: An Adaptive Retrieval Calibration Agent for Clinical Question Answering

arXiv:2609.36392v1 Announce Type: new Abstract: In diseases where clinical guidelines are incomplete, contested, or mutually contradictory, knowledge completeness and dynamic conflict-aware synthesis

AutoMark: Enabling Autoresearch to Discover Better LLM Watermarks

arXiv:2609.37310v1 Announce Type: cross Abstract: With LLM watermarking being deployed commercially and now required by regulations, improving its reliability and effectiveness has become crucial. Yet

Tutorials

Benchmarking graph-based models for in-silico toxicity prediction in drug discovery

arXiv:2609.37555v1 Announce Type: new Abstract: Drug discovery is a costly and high-risk process, where toxicity-related failures remain a major cause of attrition in both preclinical and clinical sta

tutorialsarxiv-cs-lg

Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies

arXiv:2609.38155v1 Announce Type: cross Abstract: Answering questions about long videos often requires connecting events involving the same objects across hours or days. Chronological descriptions and

Hardware

BiFE: Search-Efficient Discovery of CPU-Only Branching Policies via LLM-based Bi-Fidelity Evolution

arXiv:2609.36735v1 Announce Type: new Abstract: In branch-and-bound (B&B) for mixed-integer linear programming (MILP), branching variable selection critically impacts efficiency. Existing neural branc

hardwarearxiv-cs-ai

CAD-Native Transformer Operators for AI-Aided Engineering

arXiv:2609.36806v1 Announce Type: new Abstract: Modern engineering systems, from automobiles to aircraft, are designed by using precise, continuous parametric computer-aided design (CAD) models. Evalu

Can Multimodal Large Language Models Generate and Detect Multimodal Social Media Fake News?

arXiv:2609.35809v1 Announce Type: cross Abstract: The rapid advancement of generative AI raises concerns about the misuse of Multimodal LLMs (MLLMs) for large-scale disinformation campaigns on social

Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

arXiv:2609.36307v1 Announce Type: new Abstract: Partial Least Squares (PLS) regression extracts a few outcome-aligned directions in a high-dimensional X and is widely used across applied science, but

Codebook-Guided Cross-Modal Knowledge Distillation for Structurally Heterogeneous Features

arXiv:2609.37243v1 Announce Type: cross Abstract: Cross-modal knowledge distillation transfers knowledge from a teacher modality to a student modality. Existing feature-level alignment methods typical

Agents

Complementary Retrieval-Augmented Prompting for Consistent Long-Form Video Generation

arXiv:2609.37407v1 Announce Type: new Abstract: While recent video foundation models excel at generating high-quality short videos, long-form video generation remains a critical challenge, where a maj

agentsarxiv-cs-cv

Concealing LLM-Based Multi-Agent Topology via Phantom Structure Injection

arXiv:2609.37567v1 Announce Type: cross Abstract: Driven by the rapid advancement of large language models (LLMs), LLM-based multi-agent systems (MAS) have emerged as a powerful paradigm for collabora

Cross-attention encoding models reveal dynamic spatiotemporal routing across human higher visual cortex

arXiv:2609.36366v1 Announce Type: cross Abstract: Understanding how the brain parses actions and events from time-varying natural inputs is a central challenge in neuroscience. Recent work has used de

Cryo-EM as a Stochastic Inverse Problem

arXiv:2509.05541v2 Announce Type: replace-cross Abstract: Cryo-electron microscopy (Cryo-EM) enables high-resolution imaging of biomolecules, but structural heterogeneity remains a major challenge in

Applications

Designing a Boundary Negotiating Artifact for Collaborative Socio-Technical Sense-Making in AI Regulatory Sandboxes

arXiv:2609.37109v1 Announce Type: cross Abstract: The rapid, unpredictable advancements in AI system capabilities has seen regulators take adaptive and experimental approaches to policymaking. Establi

applicationsarxiv-cs-ai

Dimensionally consistent surrogate modelling through dimensional analysis and harmonic expansions

arXiv:2609.38094v1 Announce Type: new Abstract: Dimensional homogeneity is a fundamental constraint on physically meaningful models, requiring invariance under changes of units. We present a data-driv

DisCoMBO: Steering Expert-in-the-Loop Black Box Optimization via Distributional Conformance

arXiv:2609.36472v1 Announce Type: new Abstract: Sequential Model-Based Optimization (SMBO) traditionally relies on Bayesian or ensembling surrogates for uncertainty quantification. While historically

Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents

arXiv:2502.04492v3 Announce Type: replace Abstract: The advancement of LLMs and their accessibility have triggered renewed interest in multi-agent reinforcement learning as robust and adaptive framewo

safetyarxiv-cs-cl

EvoMO-SR: Multiobjective LLM-based Evolution of Symbolic Expressions with substructure guidance

arXiv:2609.36187v1 Announce Type: new Abstract: Symbolic Regression (SR) is a data-driven method for scientific discovery which searches for interpretable analytical relationships within data. Recentl

Fair Policy Optimization in Major-Minor Weakly Coupled Markov Decision Processes

arXiv:2609.36174v1 Announce Type: new Abstract: We consider fair resource allocation in sequential decision-making environments modeled as major-minor weakly coupled Markov decision processes (M2WCMDP

safetyarxiv-cs-lg

FairDiff: Mitigating the Self-Reinforcing Matthew Effect in Diffusion Recommender Models

arXiv:2609.36671v1 Announce Type: new Abstract: While the 'Matthew Effect' and filter bubbles are widely recognized outcome-level biases in recommender systems, we reveal that Diffusion Recommender Mo

FlowMap-OPD: Rollout--Kernel Separation for On-Policy Distillation of Few-Step Flow-Map Generators

arXiv:2609.37851v1 Announce Type: new Abstract: Few-step flow-map generators, including MeanFlow and consistency models, enable efficient sampling through long-range transport, yet their on-policy dis

safetyarxiv-cs-cv

Fooling Algorithms in Non-Stationary Bandits using Belief Inertia

arXiv:2511.05620v2 Announce Type: replace Abstract: We study worst-case dynamic regret of specific multi-armed bandit algorithms on piecewise-stationary instances with at most one breakpoint. Our cons

Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps

arXiv:2602.12624v2 Announce Type: replace-cross Abstract: Diffusion-based generative models have achieved remarkable performance across various domains, yet their practical deployment is often limited

researcharxiv-cs-cv

Industry

FTC reportedly investigating OpenAI, Anthropic over potential consumer risks

The U.S. Federal Trade Commission is reportedly investigating OpenAI Group PBC, Anthropic PBC and other artificial intelligence providers. The New York Times today cited a source as saying that the pr

industrysiliconangle

GARDiff: Graph-Aligned Residual Diffusion for Probabilistic Multivariate Time-Series Forecasting

arXiv:2609.37694v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for probabilistic multivariate time-series forecasting by modeling complex conditional distribut

Gondola: Grounded Vision Language Planning for Robotic Manipulation

arXiv:2506.11261v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have shown promising progress in robotic manipulation. However, directly mapping visual observations and l