Search: “framework”

PrefPI: Preference-Guided Steering into Out-of-Distribution Behaviors

arXiv:2609.40165v1 Announce Type: cross Abstract: We present PrefPI (Preference-Guided Policy Iteration), an iterative framework for steering pretrained generative robot policies using only relative p

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QuantCode Model: Specializing Language Models for Executable Algorithmic Trading Code

DGX agent

arXiv:2609.39420v1 Announce Type: new Abstract: Large language models are strong general-purpose code generators, but executable algorithmic trading remains a demanding specialization target: a model

model-releasesarxiv-cs-cl

1 Oct 2026

RankEvolve: A Reliable Multi-Agent Auto-Research Harness for Evolving Ranking Models

arXiv:2609.39551v1 Announce Type: new Abstract: Auto-research agents, LLM systems that propose, implement, train, and evaluate model changes across iterations, promise to automate applied ML's experim

RealWorldShop: Benchmarking and Improving Conversational Shopping Agents in Real-World E-commerce

arXiv:2609.38974v1 Announce Type: new Abstract: Large language models are reshaping ecommerce from static recommenders into interactive shopping assistants, yet real-world shopping requires session-le

Recovering Off-Policy Supervision for Speculative Decoding

arXiv:2609.38795v1 Announce Type: new Abstract: Block drafters for speculative decoding are commonly trained on corpora written by external models, where a single off-policy token invalidates supervis

safetyarxiv-cs-cl

ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving

arXiv:2609.39245v1 Announce Type: new Abstract: In interactive scenarios, an autonomous driving system is required to generate ego actions under the influence of other agents' behaviors. Existing Worl

safetyarxiv-cs-ro

RW-Flow: One-Step Generation on Compact Manifolds via Wasserstein Gradient Flows

arXiv:2609.39271v1 Announce Type: new Abstract: Manifold-valued data, and consequently the distributions they induce, are prevalent across many domains, ranging from the locations of geospatial events

researcharxiv-cs-lg

SceneJail: Exploiting Video Scenario Context to Jailbreak Multimodal LLMs

arXiv:2609.38899v1 Announce Type: cross Abstract: Video Multimodal Large Language Models (Video-MLLMs) support reasoning over video inputs, yet remain vulnerable to jailbreak attacks that elicit polic

Security-Enhanced Seed-Based Weight Quantization for Large Language Models

arXiv:2609.38477v1 Announce Type: cross Abstract: Large language models (LLMs) incur substantial storage, memory-bandwidth and energy costs, motivating compact weight representations. Existing seed-ba

researcharxiv-cs-ai

Semantic Misalignment in Vision-Language Models under Perceptual Degradation

arXiv:2601.08355v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) are increasingly deployed in autonomous driving and embodied AI systems, where reliable perception is critical for saf

safetyarxiv-cs-cv

SkillFM: Generating Skills for LLM Agents via Latent Flow Matching

arXiv:2609.39382v1 Announce Type: new Abstract: Textual skills provide reusable guidance for large language model agents, but existing approaches often rely on manually curated skill banks or reinforc

agentsarxiv-cs-ai

Applications

SOLAR: SVD-Optimized Lifelong Attention for Recommendation

arXiv:2603.02561v2 Announce Type: replace-cross Abstract: Attention mechanism remains the defining operator in Transformers since it provides expressive global credit assignment, yet its quadratic cos

applicationsarxiv-cs-cv

Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks

arXiv:2609.39549v1 Announce Type: cross Abstract: As Large Language Model (LLM) agents are increasingly deployed in complex environments, multi-turn interaction attacks have become a significant secur

The Geometry of Harmfulness in Multi-Turn Attacks

model-releasesarxiv-cs-cl

arXiv:2609.38389v1 Announce Type: cross Abstract: Large language models (LLMs) remain vulnerable to adversarial attacks that circumvent safety alignment to elicit harmful outputs. It remains unclear h

Tool-Policy Co-Design for Powder Weighing in Laboratory Automation

arXiv:2609.39797v1 Announce Type: new Abstract: Autonomous powder weighing is one of many bottlenecks in laboratory automation due to the complex, non-linear dynamics of heterogeneous materials. Robot

safetyarxiv-cs-ro

URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centres

arXiv:2602.10124v2 Announce Type: replace-cross Abstract: Cycling is reported by an average of 35% of adults at least once per week across 28 countries, and as vulnerable road users directly exposed t

researcharxiv-cs-cv

WARP: A Unified Benchmark for Invisible Image Watermarking -- Robustness and Protection Against Attacks

arXiv:2609.40031v1 Announce Type: cross Abstract: Digital image watermarking is increasingly critical in media contexts, as emerging regulations and industry practices require marking AI-generated con

Where MLLMs Fail and Why: Causal Task Decomposition for Capability Failure Diagnosis

arXiv:2609.38851v1 Announce Type: cross Abstract: End-to-end accuracy on compositional tasks records how often MLLMs fail, but cannot distinguish whether a failure reflects an intrinsic deficit in the

A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses

arXiv:2609.37788v1 Announce Type: cross Abstract: Rubrics support the structured evaluation of language models. We propose a rubric for assessing expressed clinical reasoning in model responses, drawi

Agentic AI for Scalable and Robust Optical Systems Control

arXiv:2602.20144v2 Announce Type: replace-cross Abstract: We present AgentOptics, an agentic AI framework for high-fidelity, autonomous optical system control built on the Model Context Protocol (MCP)

Agentic Federated Learning: Rule-Based Client and Server Agents for Adaptive Training

arXiv:2609.35914v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it suitable for privacy-sensi

agentsarxiv-cs-lg

AnthroDial: Benchmarking LLM Anthropomorphism in Autonomous Social Interaction

arXiv:2609.37853v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as social agents, yet credible human-like interaction requires more than fluent responses or pers

agentsarxiv-cs-cl

Beyond Lip Sync: Reference-Grounded Oral Refinement for Audio-Driven Portrait Animation

arXiv:2609.38019v1 Announce Type: new Abstract: We present RGOR (Reference-Grounded Oral Refinement), an audio-driven lip-sync framework that renders the mouth of the specific person being dubbed rath

Byzantine-Robust Federated Representation Learning

arXiv:2609.36660v1 Announce Type: new Abstract: We study federated learning (FL) with adversarial clients, where the goal is to minimize the average loss of the honest (non-adversarial) clients withou

CI-PINN: Causal Integral Physics-Informed Neural Network for Solving Evolution Equations

arXiv:2609.36615v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) solve partial differential equations (PDEs) by incorporating governing physical laws into the training loss.

Local Ai

Data-Efficient Time-Dependent PDE Surrogates: Graph Neural Simulators vs. Neural Operators

arXiv:2509.06154v3 Announce Type: replace Abstract: Developing accurate, data-efficient surrogate models is central to advancing AI for Science. Neural operators (NOs), which approximate mappings betw

local-aiarxiv-cs-lg

DMA^2: Pixel-space Distribution Matching with Adversarial and Anchor Losses

arXiv:2609.38156v1 Announce Type: new Abstract: Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations hav

Local Ai

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

Equally Good, Yet Different: Benchmarking Rashomon sets in AutoML packages

arXiv:2609.36970v1 Announce Type: new Abstract: The Rashomon effect describes the existence of multiple near-optimal models that achieve comparable performance while offering fundamentally different e

Explainable Machine Learning for Multilayer Planar Winding Inductance Estimation

arXiv:2609.37211v1 Announce Type: new Abstract: Rapid and accurate self-inductance estimation for multilayer rectangle-shaped planar windings is essential for modern high-frequency power converters, y

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

researcharxiv-cs-lg

Homo-RAG: Homology-Guided Retrieval-Augmented Generation for Cross-Species Gene Function Prediction

arXiv:2608.25466v2 Announce Type: replace-cross Abstract: The functional annotation of genes in non-model organisms remains a significant challenge in computational biology, with 20-70% of sequenced g

Infrared Subtraction with Artificial Intelligence

arXiv:2609.36007v1 Announce Type: cross Abstract: We present AI-developed local infrared subtraction, building on projection to Born and EFT matching. The framework separates an integrable radiation t

Tutorials

KernelOnet: An Interpretable Neural Operator Based on Kernel Functions

arXiv:2609.35938v1 Announce Type: new Abstract: This paper proposes an interpretable neural operator framework, the Kernel Operator Network (KernelOnet), which incorporates kernel functions explicitly

tutorialsarxiv-cs-lg

Tutorials

Learning Samples Importance: Parameterizing Dual Variables in Everywhere Learning

arXiv:2609.36310v1 Announce Type: new Abstract: Everywhere learning provides a principled framework for training AI models under constraints that must hold throughout the data distribution. In the dua

tutorialsarxiv-cs-lg

LIFT: Layout-In-Future Video Generation under Large Viewpoint Change via On-Policy Self-Distillation

arXiv:2609.38146v1 Announce Type: new Abstract: We introduce LIFT, a unified image-to-video generation framework that complements camera control with Layout-In-FuTure control, enabling users to specif

safetyarxiv-cs-cv

Looped Transformers as Optimizers

arXiv:2609.37379v1 Announce Type: new Abstract: Looped Transformers provide a parameter-efficient approach to depth scaling by repeatedly applying shared Transformer blocks. Recent reasoning models ha

SAM Meets VLM: Parameter-Decoupled Full-Parameter Training for Unified Medical Reasoning and Segmentation

arXiv:2609.37283v1 Announce Type: new Abstract: Medical multimodal large language models (MLLMs) are increasingly expected not only to answer clinical questions, but also to localize the visual eviden

Sample Complexity of Equivariant Reinforcement Learning

arXiv:2609.36421v1 Announce Type: cross Abstract: Reinforcement learning (RL) is a powerful framework for robotic control, yet its practical application is often hindered by high sample complexity. Th

safetyarxiv-cs-lg

Sequence Variables: A Constraint Programming Computational Domain for Routing and Sequencing

arXiv:2510.09373v2 Announce Type: replace Abstract: Constraint Programming (CP) offers an intuitive, declarative framework for modeling Vehicle Routing Problems (VRP). While classical successor-based

researcharxiv-cs-ai

Simultaneous Neural Optimal Transport

arXiv:2609.37424v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for learning transformations between probability distributions from unpaired samples. In many a

STRIDE: Automated Evaluation of Text-to-Trajectory Alignment across Diverse Contexts

arXiv:2609.34799v2 Announce Type: replace Abstract: Language-conditioned trajectory generation is here, but its evaluation has not kept pace. Existing pedestrian trajectory metrics compare trajectorie

WitnessGym: Benchmarking Coding Agents on the Construction of Bug Witnesses

arXiv:2609.36635v1 Announce Type: cross Abstract: Bug validation asks a coding agent to produce an executable witness for a reported bug. The witness combines a concrete input with a testing harness a

World2Motion: Turning Video World Models into 3D Human Motion Generators

arXiv:2609.37004v1 Announce Type: new Abstract: We present World2Motion, a framework that generates scene-aware 3D human motion and corresponding video from a single image and a text prompt. While exi

AD-SAM: Adapting the Segment Anything Model for Semantic Segmentation in Autonomous Driving

arXiv:2510.27047v2 Announce Type: replace Abstract: This paper presents the Autonomous Driving Segment Anything Model (AD-SAM), a foundation-model adaptation framework for semantic segmentation in aut

agentsarxiv-cs-cv

Agnostic Smoothed Online Regression with Adversarial Responses

arXiv:2609.32478v1 Announce Type: cross Abstract: We study smoothed online prediction with bounded adversarial responses. This widely studied framework bridges i.i.d. sampling and adversarial covariat

Audio-JEPA: Joint-Embedding Predictive Architecture for Audio Representation Learning

arXiv:2507.02915v2 Announce Type: replace-cross Abstract: Building on the Joint-Embedding Predictive Architecture (JEPA) paradigm, a recent self-supervised learning framework that predicts latent repr

Automated Species Identification in Camera Trap Images for Wildlife Conservation

arXiv:2609.35420v1 Announce Type: new Abstract: Wildlife conservation involves protecting, preserving, and managing wildlife species and their habitats. With today's rapid pace of human development, c