Search: “papers”

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge

local-aiarxiv-cs-ai

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PAC learning PDFA from data streams

DGX agent

arXiv:2604.02244v3 Announce Type: replace-cross Abstract: This is an extended version of our publication Learning state machines from data streams: A generic strategy and an improved heuristic, Intern

researcharxiv-cs-lg

14 Apr 2026

Pair2Scene: Learning Local Object Relations for Procedural Scene Generation

arXiv:2604.11808v1 Announce Type: new Abstract: Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relation

local-aiarxiv-cs-cv

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP

arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p

PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

arXiv:2412.11390v3 Announce Type: replace-cross Abstract: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. Howeve

safetyarxiv-cs-lg

Physical Commonsense Reasoning for Lower-Resourced Languages and Dialects: a Study on Basque

arXiv:2602.14812v3 Announce Type: replace Abstract: Physical commonsense reasoning represents a fundamental capability of human intelligence, enabling individuals to understand their environment, pred

researcharxiv-cs-cl

Poisoning with A Pill: Circumventing Detection in Federated Learning

arXiv:2407.15389v2 Announce Type: replace Abstract: Without direct access to the client's data, federated learning (FL) is well-known for its unique strength in data privacy protection among existing

researcharxiv-cs-lg

PokeRL: Reinforcement Learning for Pokemon Red

model-releasesarxiv-cs-lg

arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei

Agents

PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tables

arXiv:2412.04272v5 Announce Type: replace-cross Abstract: In recent years, table reasoning has garnered substantial research interest, particularly regarding its integration with Large Language Models

agentsarxiv-cs-ai

Preference-Agile Multi-Objective Optimization for Real-time Vehicle Dispatching

arXiv:2604.10664v1 Announce Type: new Abstract: Multi-objective optimization (MOO) has been widely studied in literature because of its versatility in human-centered decision making in real-life appli

Principles Do Not Apply Themselves: A Hermeneutic Perspective on AI Alignment

arXiv:2604.10673v1 Announce Type: new Abstract: AI alignment is often framed as the task of ensuring that an AI system follows a set of stated principles or human preferences, but general principles r

Progressive Multimodal Interaction Network for Reliable Quantification of Fish Feeding Intensity in Aquaculture

arXiv:2506.14170v3 Announce Type: replace-cross Abstract: Accurate quantification of fish feeding intensity is crucial for precision feeding in aquaculture, as it directly affects feed utilization and

Progressively Texture-Aware Diffusion for Contrast-Enhanced Sparse-View CT

arXiv:2604.11559v1 Announce Type: new Abstract: Diffusion-based sparse-view CT (SVCT) imaging has achieved remarkable advancements in recent years, thanks to its more stable generative capability. How

{Psi}-Map: Panoptic Surface Integrated Mapping Enables Real2Sim Transfer

arXiv:2604.10982v1 Announce Type: new Abstract: Open-vocabulary panoptic reconstruction is essential for advanced robotics perception and simulation. However, existing methods based on 3D Gaussian Spl

local-aiarxiv-cs-ro

Applications

Quantization Robustness to Input Degradations for Object Detection

arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th

applicationsarxiv-cs-cv

R2E-VID: Two-Stage Robust Routing via Temporal Gating for Elastic Edge-Cloud Video Inference

arXiv:2604.09681v1 Announce Type: cross Abstract: With the rapid growth of large-scale video analytics applications, edge-cloud collaborative systems have become the dominant paradigm for real-time in

Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty

arXiv:2604.10072v1 Announce Type: new Abstract: Recent advancements in the Generative Reward Model (GRM) have demonstrated its potential to enhance the reasoning abilities of LLMs through Chain-of-Tho

researcharxiv-cs-cl

Hardware

Record-Remix-Replay: Hierarchical GPU Kernel Optimization using Evolutionary Search

arXiv:2604.11109v1 Announce Type: cross Abstract: As high-performance computing and AI workloads become increasingly dependent on GPUs, maintaining high performance across rapidly evolving hardware ge

hardwarearxiv-cs-ai

Reliable and Real-Time Highway Trajectory Planning via Hybrid Learning-Optimization Frameworks

arXiv:2508.04436v2 Announce Type: replace Abstract: Autonomous highway driving involves high-speed safety risks due to limited reaction time, where rare but dangerous events may lead to severe consequ

safetyarxiv-cs-ro

Representation-Aligned Multi-Scale Personalization for Federated Learning

arXiv:2604.11278v1 Announce Type: new Abstract: In federated learning (FL), accommodating clients with diverse resource constraints remains a significant challenge. A widely adopted approach is to use

researcharxiv-cs-lg

Resilient Write: A Six-Layer Durable Write Surface for LLM Coding Agents

arXiv:2604.10842v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly rely on tool-use protocols such as the Model Context Protocol~(MCP) to read and write files on a developer's wo

ReSpinQuant: Efficient Layer-Wise LLM Quantization via Subspace Residual Rotation Approximation

arXiv:2604.11080v1 Announce Type: cross Abstract: Rotation-based Post-Training Quantization (PTQ) has emerged as a promising solution for mitigating activation outliers in the quantization of Large La

local-aiarxiv-cs-ai

Revisiting the Scale Loss Function and Gaussian-Shape Convolution for Infrared Small Target Detection

model-releasesarxiv-cs-cv

arXiv:2604.09991v1 Announce Type: new Abstract: Infrared small target detection still faces two persistent challenges: training instability from non-monotonic scale loss functions, and inadequate spat

RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin

arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap

Tutorials

Ro-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation

arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en

tutorialsarxiv-cs-ro

Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty

arXiv:2508.21322v2 Announce Type: replace Abstract: Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dyna

safetyarxiv-cs-ro

RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents

arXiv:2604.11655v1 Announce Type: cross Abstract: The rapid adoption of Large Language Models (LLMs) in interactive systems has enabled the creation of dynamic, open-ended Role-Playing Agents (RPAs).

local-aiarxiv-cs-ai

Scaling Up AI-Generated Image Detection with Generator-Aware Prototypes

arXiv:2512.12982v2 Announce Type: replace Abstract: The pursuit of a universal AI-generated image (AIGI) detector often relies on aggregating data from numerous generators to improve generalization. H

Applications

Scene Change Detection with Vision-Language Representation Learning

arXiv:2604.11402v1 Announce Type: new Abstract: Scene change detection (SCD) is crucial for urban monitoring and navigation but remains challenging in real-world environments due to lighting variation

applicationsarxiv-cs-cv

SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters

arXiv:2511.18329v3 Announce Type: replace Abstract: Scientific posters play a vital role in academic communication by presenting ideas through visual summaries. Analyzing reading order and parent-chil

SHANG++: Robust Stochastic Acceleration under Multiplicative Noise

model-releasesarxiv-cs-lg

arXiv:2603.09355v1 Announce Type: cross Abstract: Under the multiplicative noise scaling (MNS) condition, original Nesterov acceleration is provably sensitive to noise and may diverge when gradient no

Sheaf Diffusion with Adaptive Local Structure for Spatio-Temporal Forecasting

arXiv:2604.11275v1 Announce Type: new Abstract: Spatio-temporal systems often exhibit highly heterogeneous and non-intuitive responses to localized disruptions, limiting the effectiveness of conventio

local-aiarxiv-cs-lg

SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation

arXiv:2305.09958v5 Announce Type: replace Abstract: Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. neighboring nod

researcharxiv-cs-lg

Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation

model-releasesarxiv-cs-ro

arXiv:2604.10548v1 Announce Type: new Abstract: Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory,

Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis

model-releasesarxiv-cs-cl

arXiv:2604.09874v1 Announce Type: new Abstract: Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world

SLALOM: Simulation Lifecycle Analysis via Longitudinal Observation Metrics for Social Simulation

arXiv:2604.11466v1 Announce Type: cross Abstract: Large Language Model (LLM) agents offer a potentially-transformative path forward for generative social science but face a critical crisis of validity

Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE

arXiv:2604.11140v1 Announce Type: new Abstract: Integrating frame-based RGB cameras with event streams offers a promising solution for robust object detection under challenging dynamic conditions. How

Spatiotemporal-Aware Bit-Flip Injection on DNN-based Advanced Driver Assistance Systems (extended version)

arXiv:2604.03753v2 Announce Type: replace-cross Abstract: Modern advanced driver assistance systems (ADAS) rely on deep neural networks (DNNs) for perception and planning. Since DNNs' parameters resid

safetyarxiv-cs-lg

Speaking to No One: Ontological Dissonance and the Double Bind of Conversational AI

arXiv:2604.10833v1 Announce Type: cross Abstract: Recent reports indicate that sustained interaction with conversational artificial intelligence (AI) systems can, in a small subset of users, contribut

SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting

arXiv:2407.20799v3 Announce Type: replace Abstract: Facial expression spotting, identifying periods where facial expressions occur in a video, is a significant yet challenging task in facial expressio

local-aiarxiv-cs-cv

Tutorials

Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation

arXiv:2604.10071v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities yet continue to suffer from hallucination, where generated

tutorialsarxiv-cs-cv

StableTTA: Training-Free Test-Time Adaptation that Improves Model Accuracy on ImageNet1K to 96%

arXiv:2604.04552v2 Announce Type: replace-cross Abstract: Ensemble methods are widely used to improve predictive performance, but their effectiveness often comes at the cost of increased memory usage

STGV: Spatio-Temporal Hash Encoding for Gaussian-based Video Representation

arXiv:2604.10910v1 Announce Type: new Abstract: 2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-ag

Stop Fixating on Prompts: Reasoning Hijacking and Constraint Tightening for Red-Teaming LLM Agents

arXiv:2604.05549v2 Announce Type: replace Abstract: With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team

safetyarxiv-cs-cl

SynthAgent: Adapting Web Agents with Synthetic Supervision

arXiv:2511.06101v3 Announce Type: replace-cross Abstract: Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored

researcharxiv-cs-ai

Tutorials

TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation

arXiv:2508.02204v4 Announce Type: replace Abstract: Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both eff

tutorialsarxiv-cs-ro

TARAC: Mitigating Hallucination in LVLMs via Temporal Attention Real-time Accumulative Connection

arXiv:2504.04099v2 Announce Type: replace-cross Abstract: Large Vision-Language Models have demonstrated remarkable capabilities, yet they suffer from hallucinations that limit practical deployment. W

researcharxiv-cs-ai

Hardware

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin

hardwarearxiv-cs-lg