Search: “models”

Causal Anomaly Detection for Lithium-Ion Battery Degradation

arXiv:2605.17334v1 Announce Type: cross Abstract: Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c

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Causal Attribution via Activation Patching

DGX agent

arXiv:2603.13652v2 Announce Type: replace Abstract: Attribution methods for Vision Transformers (ViTs) aim to identify image regions that influence model predictions, but producing faithful and well-l

local-aiarxiv-cs-cv

19 May 2026

Tutorials

CAVE: A Structured Credit Assignment Approach for Fragmented Visual Evidence Reasoning

arXiv:2605.16416v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual i

tutorialsarxiv-cs-ai

CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs

arXiv:2502.18663v3 Announce Type: replace Abstract: This paper is the second in a series of studies on developing efficient artificial intelligence-based approaches to pathfinding on extremely large g

CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?

arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions

Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction

arXiv:2605.16832v1 Announce Type: new Abstract: Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud en

Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis

arXiv:2605.18451v1 Announce Type: new Abstract: Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, an

CommitDistill: A Lightweight Knowledge-Centric Memory Layer for Software Repositories

arXiv:2605.18284v1 Announce Type: cross Abstract: Software repositories accumulate large amounts of unstructured knowledge in commit messages, pull-request discussions, and issue threads, but develope

CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects

arXiv:2604.02060v2 Announce Type: replace Abstract: When told to 'cut the cake,' a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-w

Local Ai

Constrained Code Generation with Discrete Diffusion

arXiv:2605.16829v1 Announce Type: new Abstract: Discrete diffusion models are a powerful, emerging paradigm for code generation. They construct programs through iterative refinement of partially corru

local-aiarxiv-cs-cl

Content-Style Identification via Differential Independence

arXiv:2605.17827v1 Announce Type: cross Abstract: Generative analysis often models multi-domain observations as nonlinear mixtures of domain-invariant content variables and domain-specific style varia

Controlla: Learning Controllability via Graph-Constrained Latent Geometry

arXiv:2605.16603v1 Announce Type: new Abstract: Controllable multimodal generation is commonly formulated as an inference-time conditioning problem using prompts, guidance, or auxiliary modules. While

CooT: Learning to Coordinate In-Context with Coordination Transformers

arXiv:2506.23549v3 Announce Type: replace Abstract: Effective coordination among unfamiliar partners remains a major challenge in multi-agent systems. Existing approaches, such as population-based met

CoX-MoE: Coalesced Expert Execution for High-Throughput MoE Inference with AMX-Enabled CPU-GPU Co-Execution

arXiv:2605.17889v1 Announce Type: new Abstract: The Mixture-of-Experts (MoE) architecture improves computational efficiency via sparse expert activation, but throughput-oriented inference faces substa

Safety

Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generation

arXiv:2605.17807v1 Announce Type: cross Abstract: Text-to-Image (T2I) generation has achieved remarkable progress in recent years. Meanwhile, reinforcement learning methods, particularly those based o

safetyarxiv-cs-ai

D^2Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning

arXiv:2605.17037v1 Announce Type: cross Abstract: Reinforcement learning (RL) has demonstrated potential for enhancing reasoning in large language models (LLMs). However, effective RL training, which

Decoupled Conformal Optimisation: Efficient Prediction Sets via Independent Tuning and Calibration

arXiv:2605.18354v1 Announce Type: new Abstract: Bayesian conformal optimisation methods often use the same held-out data both to search for efficient prediction sets and to certify coverage or risk. T

Deep learning-based compression of giga-resolution whole slide images

arXiv:2605.17668v1 Announce Type: new Abstract: Implementation of digital pathology leads to an increased number of whole slide images (WSIs). The large size of WSIs is challenging. Today, WSIs are co

DexHoldem: Playing Texas Hold'em with Dexterous Embodied System

arXiv:2605.18727v1 Announce Type: cross Abstract: Evaluating embodied systems on real dexterous hardware requires more than isolated primitive skills: an agent must perceive a changing tabletop scene,

Safety

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap

arXiv:2508.04149v2 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with human preferences is a critical challenge in AI research. While methods like Reinforcement Learning

safetyarxiv-cs-ai

Double-Calibration: Towards Reliable LLMs via Calibrating Knowledge and Reasoning Confidence

arXiv:2601.11956v2 Announce Type: replace-cross Abstract: Reliable reasoning in Large Language Models (LLMs) is challenged by their propensity for hallucination. While augmenting LLMs with Knowledge G

Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection

model-releasesarxiv-cs-cl

arXiv:2605.18512v1 Announce Type: new Abstract: In-context learning (ICL) is highly sensitive to which demonstrations appear in the prompt, but selecting them is expensive because the space of possibl

Hardware

Efficient 3D Content Reconstruction and Generation

arXiv:2605.18052v1 Announce Type: new Abstract: Automatic 3D content creation seeks to replace labor-intensive modeling and scanning pipelines with systems that can synthesize or recover 3D assets dir

hardwarearxiv-cs-cv

Efficient and Noise-Tolerant PAC Learning of Multiclass Linear Classifiers

arXiv:2605.18662v1 Announce Type: new Abstract: Noise-tolerant PAC learning of linear models has been of central interests in machine learning community since the last century. In recent years, many c

researcharxiv-cs-lg

Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

arXiv:2605.18674v1 Announce Type: new Abstract: Generalized planning aims to learn policies that generalize across collections of instances within a classical planning domain. Recent Graph Neural Netw

Embedded ConvNet Ensembles: A Lightweight Approach to Recognize Arabic Handwritten Characters

arXiv:2605.18060v1 Announce Type: new Abstract: Arabic Handwritten Character Recognition (AHCR) has recently advanced significantly with deep Convolutional Neural Networks (ConvNets). However, many mo

EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

arXiv:2508.07292v3 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians progressively acquire, compare, and verify local visual evidence before reaching a

Error-Decomposed Class-Conditional Fusion for Statistically Guaranteed Hard-Category Robust Perception

arXiv:2605.17591v1 Announce Type: new Abstract: Aggregate object detection metrics inherently mask catastrophic and repeatable failures in operationally critical, long-tail minority classes. This pape

Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps

arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de

Applications

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation

arXiv:2502.04055v2 Announce Type: replace Abstract: Current evaluations of synthetic tabular data mainly focus on how well joint distributions are modeled, often overlooking the assessment of their ef

applicationsarxiv-cs-lg

Finite-Particle Rates for Regularized Stein Variational Gradient Descent

arXiv:2602.05172v2 Announce Type: replace-cross Abstract: We derive finite-particle rates for the regularized Stein variational gradient descent (R-SVGD) algorithm introduced by He et al. (2024) that

Local Ai

FishBack: Pullback Fisher Geometry for Optimal Activation Steering in Transformers

arXiv:2605.17231v1 Announce Type: cross Abstract: Activation steering methods modify intermediate representations of language models to control output behavior, but universally assume the activation s

local-aiarxiv-cs-cl

Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission

model-releasesarxiv-cs-cl

arXiv:2602.03784v2 Announce Type: replace Abstract: Long-context LLM agents often struggle with growing token, memory, and latency costs, making efficient context compression essential for practical d

Agents

Fixed External Cameras as Common Prior Maps for Active 3D Scene Graph Generation

arXiv:2605.18184v1 Announce Type: cross Abstract: Commonly available prior information, such as BIM models, floor plans, and remote sensing images, can provide valuable geometric and semantic context

agentsarxiv-cs-ai

FlowMixer: A Depth-Agnostic Neural Architecture for Interpretable Spatiotemporal Forecasting

arXiv:2505.16786v2 Announce Type: replace Abstract: We introduce FlowMixer, a single-layer neural architecture that leverages constrained matrix operations to model structured spatiotemporal patterns

researcharxiv-cs-lg

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

arXiv:2605.17373v1 Announce Type: cross Abstract: AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies ra

Focused Forcing: Content-Aware Per-Frame KV Selection for Efficient Autoregressive Video Diffusion

arXiv:2605.18346v1 Announce Type: cross Abstract: Recent advances in autoregressive video diffusion have enabled sequential and streaming video generation. However, long-horizon generation requires in

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking

arXiv:2601.06163v2 Announce Type: replace Abstract: The widespread adoption of text-to-image (T2I) diffusion models has raised concerns about their potential to generate copyrighted, inappropriate, or

From BERT to T5: A Study of Named Entity Recognition

arXiv:2605.18462v1 Announce Type: new Abstract: Named entity recognition (NER) has been one of the essential preliminary steps in modern NLP applications. This report focuses on implementing the NER t

researcharxiv-cs-cl

From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning

arXiv:2605.17162v1 Announce Type: new Abstract: This paper investigates whether shallow neural network agents can master the card game Schnapsen and challenge a strong search-based baseline, RdeepBot,

Tutorials

Generating Pretraining Tokens from Organic Data for Data-Bound Scaling

arXiv:2605.17849v1 Announce Type: cross Abstract: LLM pretraining is shifting from a compute-bound to a data-bound regime, where available human (organic) text falls far short of scaling demands. Howe

tutorialsarxiv-cs-ai

Agents

Genflow Ad Studio: A Compound AI Architecture for Brand-Aligned, Self-Correcting Video Generation

arXiv:2605.16748v1 Announce Type: cross Abstract: Recent advancements in generative video models demonstrate high visual fidelity, yet their integration into enterprise environments is restricted by t

agentsarxiv-cs-ai

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis

arXiv:2507.21035v3 Announce Type: replace Abstract: Gene expression analysis holds the key to many biomedical discoveries, yet extracting insights from raw transcriptomic data remains formidable due t

Geometric Asymmetry in MoE Specialization: Functional Decorrelation and Representational Overlap

arXiv:2605.16349v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures achieve scalable capacity through sparse routing, yet the geometric structure of expert specialization remains po

GIST: Targeted Data Selection for Instruction Tuning via Coupled Optimization Geometry

arXiv:2602.18584v2 Announce Type: replace-cross Abstract: Targeted data selection has emerged as a crucial paradigm for efficient instruction tuning, aiming to identify a small yet influential subset

Graph Embedding in the Graph Fractional Fourier Transform Domain

arXiv:2508.02383v2 Announce Type: replace Abstract: Spectral graph embedding plays a critical role in graph representation learning by generating low-dimensional vector representations from graph spec

GraphMind: Theorem Selection and Conclusion Generation Framework with Dynamic GNN for LLM Reasoning

arXiv:2511.19078v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, including multi-step

GRID: Graph Representation of Intelligence Data for Security Text Knowledge Graph Construction

arXiv:2605.16714v1 Announce Type: new Abstract: Security knowledge graphs can provide computable external memory for security agents, but constructing them from long-form cyber threat intelligence (CT