Search: “framework”

Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

arXiv:2609.03860v1 Announce Type: new Abstract: Retail supply chain operations rely on coupled decision modules that must adapt as requirements evolve. LLMs offer a natural-language interface for this

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Artificial Intelligence for Energy Optimization in Data Centers

DGX agent

arXiv:2609.03716v1 Announce Type: new Abstract: Data centers are increasingly optimized by artificial intelligence and, at the same time, increasingly loaded by it. The literature treats these as two

safetyarxiv-cs-ai

4 Sept 2026

Attention Trajectories as a Diagnostic Axis for Deep Reinforcement Learning

arXiv:2511.20591v3 Announce Type: replace Abstract: The emergence and evolution of feature reliance in deep reinforcement learning agents remain poorly understood. Here, we introduce a methodological

agentsarxiv-cs-lg

Beyond Majority Vote: Multi-Perspective Adjudication for Medical Hallucination Detection

arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat

Beyond Reproducibility: Towards Security-Aware Evaluation of Research Artifacts

arXiv:2605.06508v2 Announce Type: replace-cross Abstract: Research artifacts are widely shared to support reproducibility, and artifact evaluation (AE) has become common at many leading conferences. H

BMCTrack-d: Pig re-identification and tracking via back marks in challenging camera settings

arXiv:2609.03463v1 Announce Type: new Abstract: Automated pig monitoring is essential for assessing their health, behaviour, and welfare. To date, most pig monitoring solutions operate on the group-le

researcharxiv-cs-cv

BRIDGE: An Open-Source Humanoid Platform via Morphology-Control Co-Design for Physical AI

arXiv:2609.03497v1 Announce Type: cross Abstract: Developing humanoid robots capable of leveraging human behavioral data is essential for general-purpose embodiment, yet conventional development remai

Contamination Inflates Scores but Rarely Reorders Large Language Model Leaderboards

arXiv:2609.02899v1 Announce Type: new Abstract: Benchmark contamination, the leakage of test items into training data, is widely described as a threat to the reliability of large language model (LLM)

Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks

model-releasesarxiv-cs-lg

arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent

Data-efficient Kernel Methods for Learning Hamiltonian Systems

model-releasesarxiv-cs-lg

arXiv:2509.17154v2 Announce Type: replace-cross Abstract: Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many

Distilling deep optical flow stereo methods to retrieve dense three-dimensional wind fields

arXiv:2609.03100v1 Announce Type: new Abstract: Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Tra

researcharxiv-cs-lg

Do Video Generators Track the World Across Segments? A Benchmark and Method for World-State Reasoning in Video Continuation

model-releasesarxiv-cs-cv

arXiv:2609.03673v1 Announce Type: new Abstract: Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks.

Dude: A Dual-Detection Multi-Agent System for Paper-Code Discrepancy Detection

arXiv:2609.03416v1 Announce Type: new Abstract: LLM-empowered paper-code discrepancy detection has received growing concern since the scaling of research submissions exceeds the manual review capabili

Efficient Test-Time Adaptation through Human-AI Interaction

arXiv:2609.04141v1 Announce Type: new Abstract: AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

arXiv:2609.03756v1 Announce Type: cross Abstract: We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the l

Evolving Excellence: Automated Optimization of LLM-based Agents

arXiv:2512.09108v2 Announce Type: replace-cross Abstract: Agentic AI systems built on large language models (LLMs) offer significant potential for automating complex workflows, from software developme

FPCO-Dialog: A Multi-Turn False-Premise Benchmark for Correction and Cooperation in Vision-Language Models

arXiv:2609.03331v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in multi-turn settings where users may describe visual content with incorrect assumptions. Yet e

FrameBench:A Language Understanding Benchmark Based on Frame Semantics

arXiv:2609.03370v1 Announce Type: new Abstract: In frame semantics, sentence comprehension is assumed to proceed by relating lexical meaning to background knowledge called semantic frames, thereby ena

High-Dimensional Learning Dynamics of Attention-Indexed Models

arXiv:2609.03858v1 Announce Type: new Abstract: Attention mechanisms are central to modern foundation models, yet their training dynamics remain poorly understood, especially when the attention matric

safetyarxiv-cs-lg

Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

arXiv:2601.08955v3 Announce Type: replace-cross Abstract: Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act wit

safetyarxiv-cs-ai

IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks

arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our

Inferring Affective Consciousness in an Artificial Agent: A Case Study

arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti

Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach

arXiv:2609.04028v1 Announce Type: cross Abstract: The geometric morphology of deposited filaments can significantly influence the structural performance and stability of 3D concrete-printed (3DCP) str

KnowVis: Knowledge-Centric Visual Summarization for Video Lectures

arXiv:2609.03742v1 Announce Type: cross Abstract: Video lectures are valuable educational resources, but their dense and lengthy formats often overwhelm novice learners. This difficulty stems from a f

researcharxiv-cs-cl

Learning Informative Prior with Infinite-Dimensional Continuous Normalizing Flow for Bayesian Inverse Problem

arXiv:2609.03343v1 Announce Type: cross Abstract: This paper addresses infinite-dimensional Bayesian inference for inverse problem of partial differential equations with model parameters in infinite-d

researcharxiv-cs-lg

Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning

arXiv:2609.04194v1 Announce Type: new Abstract: Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats the

researcharxiv-cs-cl

LevelSyn: Physical-Aware Logic Synthesis via Level-Asynchronous Graph Neural Networks

arXiv:2609.03594v1 Announce Type: cross Abstract: As integrated circuit technology scales into the nanometer regime, the traditional disconnect between logic synthesis and physical design has led to s

Masked Autoregressive Speech Enhancement with Continuous Neural Audio Codec Representations

arXiv:2609.03940v1 Announce Type: cross Abstract: Most previous work on speech enhancement (SE) based on masked generative modeling relied on discrete token representations of audio signals, obtained

No-Regret Bayesian Optimization with Finite-Library Input-Warped Kernels

arXiv:2609.02993v1 Announce Type: new Abstract: Gaussian-process Bayesian optimization (GP-BO) excels at black-box optimization of costly functions, e.g., hyperparameter optimization (HPO) and multi-a

agentsarxiv-cs-lg

Tutorials

OBER+: Continuity-Aware Reporting and Traceable Continuous Improvement in Outcome-Based Education

arXiv:2609.03770v1 Announce Type: cross Abstract: Institutions practising outcome-based education compute learning outcome attainment routinely, while reviews of curriculum analytics report an absence

tutorialsarxiv-cs-cl

Out-of-Distribution Generalisation with Sequence Models in Offline Multi-Agent Reinforcement Learning

arXiv:2609.03667v1 Announce Type: cross Abstract: Generalising to unseen tasks remains a fundamental challenge in offline multi-agent reinforcement learning (MARL). In this work, we present a principl

Preserving Knowledge across Space and Time for Continual Video Deepfake Detection

arXiv:2609.03446v1 Announce Type: new Abstract: The continuous emergence of high-quality video deepfakes requires detectors that continually adapt to new forgery patterns, yet existing approaches, whi

researcharxiv-cs-cv

Privacy, Robustness, and Fairness Trade-offs in Federated Intrusion Detection: Geometric Indistinguishability at the Aggregation Interface

arXiv:2609.03420v1 Announce Type: cross Abstract: Federated learning enables privacy-conscious collaboration for network intrusion detection without centralizing sensitive traffic data, yet its deploy

safetyarxiv-cs-ai

ProAct: Harnessing Streaming Motion Generation and Agentic Reasoning for Real-Time Embodied Social Interaction

model-releasesarxiv-cs-cv

arXiv:2602.14048v2 Announce Type: replace-cross Abstract: Real-time embodied social interaction places two equally demanding requirements on an agent: continuously generating fluent multimodal interac

RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting

arXiv:2609.03956v1 Announce Type: cross Abstract: Medical image inpainting has the potential to improve automated brain MRI analysis by reconstructing healthy tissue within pathological regions. We in

Applications

RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data

arXiv:2505.19030v5 Announce Type: replace Abstract: Large language models (LLMs) are increasingly expected to tackle complex tasks, driven by their expanding applications and users' growing proficienc

applicationsarxiv-cs-ai

Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAG

arXiv:2609.03749v1 Announce Type: cross Abstract: Third-party retrieval-augmented generation (RAG) marketplaces create a new auditing problem: data providers may license corpora to a RAG operator, yet

Semantic Bayesian World Models

arXiv:2609.03834v1 Announce Type: new Abstract: Knowledge graphs describe reality in crisp assertions, while the systems now consuming them, foundation models and autonomous agents, reason natively in

SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data

arXiv:2606.16276v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, alignment is no longer governed by a single universal notion o

safetyarxiv-cs-ai

Applications

Stable and Scalable Bundle Adjustment of Holistic 3D Structures

arXiv:2609.04026v1 Announce Type: new Abstract: Bundle Adjustment (BA) is a cornerstone of 3D computer vision and has benefited from decades of advances in sparse optimization and numerical methods. I

applicationsarxiv-cs-cv

Test-time adaptation for speech enhancement with an autoregressive speech prior

arXiv:2609.03622v1 Announce Type: cross Abstract: Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requirin

Applications

The Psychological Costs of Artificial Intelligence Adoption in Software Engineering

arXiv:2609.03456v1 Announce Type: cross Abstract: Artificial intelligence (AI) is increasingly used to augment software engineering (SE) workflows. While code generation remains the main use case, org

applicationsarxiv-cs-ai

To What Extent Do Large Language Models Understand Bangla Idioms?

arXiv:2609.03410v1 Announce Type: new Abstract: Idiomatic expressions are an integral part of natural language, reflecting cultural nuances and posing unique challenges for computational models, parti

Toward an~Integrated Cognitive--Ergonomic Architecture for~Human--Machine Interaction: Combining Cognitive Models with~Human Factors Ergonomics

arXiv:2609.03704v1 Announce Type: new Abstract: This paper presents an integrated approach to modeling human competencies by combining the theoretical foundations of cognitive architectures with princ

safetyarxiv-cs-ro

Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment

arXiv:2601.04736v2 Announce Type: replace Abstract: Despite remarkable capability in multi-modal understanding, deploying Multi-modal Large Language Models (MLLMs) in open-ended conversational scenari

safetyarxiv-cs-cl

Tutorials

TraveL: Transformer-based Multi-view Path Distributional Representation Learning

arXiv:2609.03427v1 Announce Type: cross Abstract: Path representation learning (PRL) for road networks has received increasing research attention, due to various path-related applications. Existing wo

tutorialsarxiv-cs-ai

Virtual Testing of Automated Driving Systems through Credible Simulations

arXiv:2609.03760v1 Announce Type: new Abstract: Simulation is increasingly used to support safety-related decision-making in road transport, particularly for the assessment and approval of automated d

safetyarxiv-cs-ro

A Survey of Transformer-based Language Models with Focus on Efficiency

arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N