Search: “framework”

On Trajectory-Aware Training for Masked Diffusion Language Models

arXiv:2609.37974v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate text by unmasking several tokens per step, but they are trained and sampled under different conditions. The mo

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One Readout, Many Repairs: Diffusion-Guided Hierarchical Search for Tool-Agent Repair

DGX agent

arXiv:2609.34879v2 Announce Type: replace Abstract: Tool agents use large language models to act through external tools, yet successfully executed calls can still leave user requests unfulfilled. Tool

model-releasesarxiv-cs-ai

30 Sept 2026

Applications

Online Versatile Incremental Learning: Towards Class and Domain-Agnostic Adaptation at Any Time

arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capt

applicationsarxiv-cs-ai

Tutorials

OntoTKGE: Ontology-Enhanced Temporal Knowledge Graph Extrapolation

arXiv:2604.05468v3 Announce Type: replace Abstract: Temporal knowledge graph (TKG) extrapolation is an important task that aims to predict future facts through historical interaction information withi

tutorialsarxiv-cs-ai

OPFL: Optimistic Verification of Federated Learning via Empirical Boundary

arXiv:2609.37011v1 Announce Type: cross Abstract: Federated learning enables multiple clients to collaboratively train models without sharing their private data. However, the lack of visibility into l

ORMA: Optimization-based Monocular 4D Reconstruction of Articulated Animals

arXiv:2609.37986v1 Announce Type: new Abstract: Recovering articulated 4D representations of animals from monocular videos remains challenging due to the large diversity of quadruped morphologies and

Orthogonal Yet Coupled: Decoupling Geometric Components for Model Merging

arXiv:2609.37564v1 Announce Type: new Abstract: Merging pretrained models has emerged as an effective approach for consolidating diverse capabilities into a single unified model. However, prevailing m

researcharxiv-cs-cl

OTT3R: Multi-View 3D Reconstruction and Fast Dataset Generation at 1% Compute

arXiv:2609.36374v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models have achieved impressive performance by scaling model and dataset size, but their cost excludes most research grou

PAIQ: Patch-Aligned Semantic Injection via Residual Rotation

arXiv:2609.37685v1 Announce Type: new Abstract: Language-aligned and self-supervised visual encoders offer complementary strengths in semantic abstraction and spatial detail. Harnessing this complemen

PHASE: Multi-Regime Modeling of Incompressible Magnetohydrodynamics

model-releasesarxiv-cs-lg

arXiv:2609.37609v1 Announce Type: new Abstract: Magnetohydrodynamics (MHD) is central to plasma modeling in astrophysics, space science, fusion, and engineering, but resolving multiscale MHD dynamics

Physics-Informed Multi-Agent Coordination for Hospital Patient Flow Optimization

arXiv:2609.37022v1 Announce Type: new Abstract: Efficient patient flow coordination across autonomous hospital departments is critical for mitigating overcrowding and balancing resource utilization. W

PoE-Fuse: Precision-Weighted Expert Fusion for Bi-Temporal Change Understanding

arXiv:2609.37485v1 Announce Type: new Abstract: Bi-temporal change understanding, which localizes and characterizes what changed between two satellite images, is central to disaster response and envir

POET: Preference Optimization for Enhanced Text-to-Image Generation

arXiv:2510.12041v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecified

safetyarxiv-cs-cl

PolyOCR-Venus: Unified OCR Foundation Models for Text-Centric Visual Intelligence

arXiv:2609.37712v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) is evolving from plain-text transcription toward general visual intelligence, requiring models to recognize, local

PowerMarketJax: A JAX Benchmark Suite for Multi-Agent Reinforcement Learning in Power Markets

arXiv:2609.37321v1 Announce Type: cross Abstract: Power markets are a natural testbed for multi-agent reinforcement learning (MARL), where multiple self-interested participants repeatedly submit bids.

Predictive Safety Curricula for Robust Legged Locomotion

arXiv:2609.37070v1 Announce Type: cross Abstract: Rare but consequential failures can persist in learned locomotion policies for legged robots even when average task performance is high, in part becau

PreferenceFlow: Test-Time Guidance of Flow-Matching Robot Policies from Human Interventions

arXiv:2609.36872v1 Announce Type: new Abstract: Flow-matching policies can represent complex robot behaviors but remain susceptible to local errors under distribution shift at deployment. Many reinfor

local-aiarxiv-cs-ro

PrimeSeeker: Capability-Oriented Supervision for Deep Search Agents

arXiv:2609.35816v1 Announce Type: cross Abstract: Large language model search agents are often trained with synthetic questions whose difficulty is increased through larger evidence graphs, additional

Privy to the Foil: Recasting Value Estimation with a Self-Privileged Critic for RLVR

arXiv:2609.37825v1 Announce Type: cross Abstract: Assigning credit to intermediate steps remains a central challenge in training Large Language Models (LLMs) on multi-step reasoning tasks with sparse

Probability is Not Enough: Exploring and Counting Divergent Tokens for Reasoning Uncertainty Quantification in LLMs

arXiv:2609.38070v1 Announce Type: new Abstract: As the chain-of-thought reasoning capabilities of large language models improve, evaluating and calibrating their reasoning confidence is becoming incre

ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation

arXiv:2609.37632v1 Announce Type: cross Abstract: Time series imputation has progressed from statistical and deep learning approaches to diffusion-based models, which have shown strong recent performa

Proofs Without Nominals: Godel's Ontological Argument, its Shallow Embedding, and the Open Questions of the Monatshefte Notes

arXiv:2609.36279v1 Announce Type: cross Abstract: The shallow embedding of higher-order modal logic in classical higher-order logic, used in Benzmuller and Scott's Notes on Godel's and Scott's variant

Hardware

Purlin: Separating Orchestration from the Datapath of Collectives

arXiv:2609.36954v1 Announce Type: cross Abstract: Distributed inference depends on GPU collective communication that must keep pace with evolving hardware and specialized workloads. However, existing

hardwarearxiv-cs-ai

PyroStack: A Multi-Band Spatio-Temporal Sub-Daily Dataset for Wildfires in the United States

arXiv:2609.36315v1 Announce Type: cross Abstract: Wildfires are an increasing hazard to ecosystems, air quality, and human systems, creating a growing need for datasets that support systematic develop

QuantMLA: Function-Aligned Dual-Path Quantization for Low-Bit MLA KV Caching

model-releasesarxiv-cs-cl

arXiv:2609.36760v1 Announce Type: cross Abstract: Multi-Head Latent Attention (MLA) enables expressive multi-head attention with compact caches for its content and decoupled RoPE paths, yet cache memo

Quantum Fidelity Landscape-Guided Prior Calibration for Single-Circuit QGAN Image Generation

arXiv:2609.36702v1 Announce Type: cross Abstract: Quantum Generative Adversarial Networks (QGANs) have emerged as representative generative models in the Noisy Intermediate-Scale Quantum (NISQ) era an

researcharxiv-cs-cv

Applications

Quantum Geometry of Data

arXiv:2507.21135v2 Announce Type: replace Abstract: We demonstrate how Quantum Cognition Machine Learning (QCML) encodes data as quantum geometry. In QCML, features of the data are represented by lear

applicationsarxiv-cs-lg

Question-Specific Knowledge Graphs for Efficient Visual Reasoning

arXiv:2609.35942v1 Announce Type: new Abstract: Recent work in visual question answering has shown that vision-language models can exhibit strong reasoning capabilities by translating visual inputs in

safetyarxiv-cs-cl

RA-CFGCache: From Branch-Level Criteria to Guided-Risk Control under Classifier-Free Guidance

arXiv:2609.36433v1 Announce Type: new Abstract: Diffusion models enable high-quality visual generation, but iterative denoising remains computationally expensive, especially under classifier-free guid

safetyarxiv-cs-cv

RAEGNet: Relation-Aware Evidence Graph Network for Harm-Aware Multimodal Fake News Detection

arXiv:2609.36902v1 Announce Type: new Abstract: Existing multimodal fake news detection methods often introduce external information to assist detection. However, most of them rely on entity-level ret

researcharxiv-cs-cl

Real2Gym: Building Gyms from Videos, Bringing Skills to Robots

arXiv:2609.37089v1 Announce Type: new Abstract: Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, execu

safetyarxiv-cs-cv

REALHOP: Rethinking Multi-Hop Reasoning Evaluation via Behavioral Auditing

arXiv:2609.36984v1 Announce Type: new Abstract: Complex questions often require multi-hop reasoning that connects facts distributed across sources or distant regions of a long context through intermed

ReCAP: Retrieval-Guided Capability Reuse for Multimodal Continual Instruction Tuning

arXiv:2609.37889v1 Announce Type: new Abstract: Multimodal continual instruction tuning (MCIT) aims to enable multimodal large language models to acquire new capabilities from sequential tasks while p

ReCaVSR: One-Step Streaming Diffusion Video Super-Resolution with Recycled Latents and Learned Cache Routing

arXiv:2609.37831v1 Announce Type: new Abstract: Real-time diffusion-based video super-resolution (VSR) is in high demand for online streaming, yet stringent latency requirements often compromise gener

local-aiarxiv-cs-cv

ReF-HIL: Shaping the Critic around Human Action Neighborhoods for Efficient Human-in-the-Loop Reinforcement Learning

arXiv:2609.37131v1 Announce Type: new Abstract: Human-in-the-loop reinforcement learning (HIL-RL) offers a promising route to efficient training of robotic manipulation policies by combining autonomou

safetyarxiv-cs-ro

Reference-Guided Machine Unlearning

arXiv:2603.11210v2 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specific training data from a model while preserving its general utility. In vision, many approxi

researcharxiv-cs-lg

Tutorials

Reimagine Video Dynamics

arXiv:2609.36496v1 Announce Type: new Abstract: Most video editing methods focus on changing the appearance of the source video, while offering limited control over its dynamics. We introduce Reimagin

tutorialsarxiv-cs-cv

Hardware

RelayVSR: Large-Small Model Collaboration for Efficient Real-World Video Super-Resolution

arXiv:2609.37850v1 Announce Type: new Abstract: Large generative models can recover realistic detail in real-world video super-resolution (VSR), but processing an entire video with them is computation

hardwarearxiv-cs-cv

ReLMem: Learning Recurrent Memory for Longitudinal EHR Modeling

arXiv:2609.37587v1 Announce Type: cross Abstract: Longitudinal electronic health record (EHR) modeling requires integrating new visits with an expanding patient history. Yet the continual accumulation

Agents

ReMem: Rethinking Perception and Memory in Long-Context Recommendation Agents

arXiv:2609.37311v1 Announce Type: new Abstract: Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative age

agentsarxiv-cs-ai

Replication Failure and Trivial Baselines in Road-Level Crash Prediction

model-releasesarxiv-cs-lg

arXiv:2609.35917v1 Announce Type: new Abstract: Graph neural networks are increasingly applied to road-level crash prediction, but the stability of their reported gains has received little scrutiny. W

RepoMAS: Solving Progressively Specified Tasks with Issue-Driven Multi-Agent Systems

arXiv:2609.32490v2 Announce Type: replace Abstract: LLM-based multi-agent systems (MASs) have shown strong potential for solving complex tasks, but most assume that task requirements are sufficiently

Representation by Design in Generation: Cross-View Class-Token Alignment in Diffusion Transformers

arXiv:2609.36348v1 Announce Type: cross Abstract: Generative and representation learning remain asymmetrically connected: semantic representations are used to improve diffusion generation, whereas the

Reprogramming Vision-Language Models via Structured Prompt Reparameterization

arXiv:2609.36680v1 Announce Type: new Abstract: Visual reprogramming adapts pretrained models to downstream tasks by modifying their input and output interfaces while keeping the backbone fixed. In vi

researcharxiv-cs-cv

ResComEmb: Effective and Efficient Multimodal Embedding via Residual Homogeneity Compression

arXiv:2609.37225v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential for universal multimodal representation learning. However, existing methods eithe

RESCUE: Repairing Language Model Errors to Sparse Circuits via Reinforcement Learning

arXiv:2609.36813v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong general capabilities that mechanistic interpretability has attributed to sparse computational circuits. Howe

local-aiarxiv-cs-lg

Resolving the Missing Financial Data Crisis: A Generative AI Pipeline for SEC 10-K Extraction

model-releasesarxiv-cs-cl

arXiv:2609.35864v1 Announce Type: new Abstract: SEC 10-K filings contain substantial financial information that is not consistently captured in structured datasets, creating a missing-data problem aff

Applications

Rethinking Multimodal Fake News Detection in the Generative AI Era

arXiv:2609.36850v1 Announce Type: new Abstract: Generative content is increasingly entering the production and dissemination of news, transforming fake news from manually fabricated or simply manipula

applicationsarxiv-cs-cl