Search: “llm”

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation

model-releasesarxiv-cs-cv

arXiv:2504.14988v3 Announce Type: replace Abstract: Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated remarkable multimodal perception capabilities, garnering significant a

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Agents

Beyond Fluency: Toward Reliable Trajectories in Agentic IR

DGX agent

arXiv:2604.04269v2 Announce Type: replace Abstract: Information Retrieval is shifting from passive document ranking toward autonomous agentic workflows that operate in multi-step Reason-Act-Observe lo

agentsarxiv-cs-ai

14 Apr 2026

Beyond Reconstruction: Reconstruction-to-Vector Diffusion for Hyperspectral Anomaly Detection

arXiv:2604.11390v1 Announce Type: new Abstract: While Hyperspectral Anomaly Detection (HAD) excels at identifying sparse targets in complex scenes, existing models remain trapped in a scalar 'reconstr

Can Large Language Models Infer Causal Relationships from Real-World Text?

arXiv:2505.18931v4 Announce Type: replace Abstract: Understanding and inferring causal relationships from texts is a core aspect of human cognition and is essential for advancing large language models

Hardware

CASK: Core-Aware Selective KV Compression for Reasoning Traces

arXiv:2604.10900v1 Announce Type: new Abstract: In large language models performing long-form reasoning, the KV cache grows rapidly with decode length, creating bottlenecks in memory and inference sta

hardwarearxiv-cs-ai

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

arXiv:2509.00891v3 Announce Type: replace Abstract: Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse

Consensus-based Recursive Multi-Output Gaussian Process

arXiv:2604.10146v1 Announce Type: new Abstract: Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distri

agentsarxiv-cs-lg

Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Using a Large Language Model

arXiv:2604.11287v1 Announce Type: new Abstract: Background: Large language models (LLMs) have been explored as tools for generating personalized exercise prescriptions, yet the consistency of outputs

Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

arXiv:2604.10344v1 Announce Type: new Abstract: The classical approach to detecting depression from vision emphasizes interpretable features, such as facial expression, and classifiers such as the Sup

Cooperation in Human and Machine Agents: Promise Theory Considerations

arXiv:2604.10505v1 Announce Type: new Abstract: Agent based systems are more common than we may think. A Promise Theory perspective on cooperation, in systems of human-machine agents, offers a unified

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2502.11008v2 Announce Type: replace Abstract: Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this

Critical-CoT: A Robust Defense Framework against Reasoning-Level Backdoor Attacks in Large Language Models

arXiv:2604.10681v1 Announce Type: cross Abstract: Large Language Models (LLMs), despite their impressive capabilities across domains, have been shown to be vulnerable to backdoor attacks. Prior backdo

CUTEv2: Unified and Configurable Matrix Extension for Diverse CPU Architectures with Minimal Design Overhead

arXiv:2604.11615v1 Announce Type: cross Abstract: Matrix extensions have emerged as an essential feature in modern CPUs to address the surging demands of AI workloads. However, existing designs often

CWCD: Category-Wise Contrastive Decoding for Structured Medical Report Generation

arXiv:2604.10410v1 Announce Type: new Abstract: Interpreting chest X-rays is inherently challenging due to the overlap between anatomical structures and the subtle presentation of many clinically sign

Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers

arXiv:2604.11507v1 Announce Type: cross Abstract: Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments. This shift

DERM-3R: A Resource-Efficient Multimodal Agents Framework for Dermatologic Diagnosis and Treatment in Real-World Clinical Settings

arXiv:2604.09596v1 Announce Type: new Abstract: Dermatologic diseases impose a large and growing global burden, affecting billions and substantially reducing quality of life. While modern therapies ca

Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction

arXiv:2604.10786v1 Announce Type: cross Abstract: Narrative understanding requires multidimensional semantic structures. This study investigates whether BERT embeddings encode dimensions of fictional

DuET: Dual Execution for Test Output Prediction with Generated Code and Pseudocode

arXiv:2604.11514v1 Announce Type: cross Abstract: This work addresses test output prediction, a key challenge in test case generation. To improve the reliability of predicted outputs by LLMs, prior ap

researcharxiv-cs-cl

Duration-Informed Workload Scheduler

arXiv:2604.09599v1 Announce Type: cross Abstract: High-performance computing systems are complex machines whose behaviour is governed by the correct functioning of its many subsystems. Among these, th

Dynamic Adaptive Attention and Supervised Contrastive Learning: A Novel Hybrid Framework for Text Sentiment Classification

arXiv:2604.10459v1 Announce Type: new Abstract: The exponential growth of user-generated movie reviews on digital platforms has made accurate text sentiment classification a cornerstone task in natura

researcharxiv-cs-cl

Emergent Social Structures in Autonomous AI Agent Networks: A Metadata Analysis of 626 Agents on the Pilot Protocol

arXiv:2604.09561v1 Announce Type: cross Abstract: We present the first empirical analysis of social structure formation among autonomous AI agents on a live network. Our study examines 626 agents -- p

Empowering Video Translation using Multimodal Large Language Models

arXiv:2604.11283v1 Announce Type: new Abstract: Recent developments in video translation have further enhanced cross-lingual access to video content, with multimodal large language models (MLLMs) play

Examining EAP Students' AI Disclosure Intention: A Cognition-Affect-Conation Perspective

arXiv:2604.10991v1 Announce Type: cross Abstract: The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic inte

Exploring the impact of fairness-aware criteria in AutoML

arXiv:2604.10224v1 Announce Type: cross Abstract: Machine Learning (ML) systems are increasingly used to support decision-making processes that affect individuals. However, these systems often rely on

Fake-HR1: Rethinking Reasoning of Vision Language Model for Synthetic Image Detection

arXiv:2602.10042v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability

Fatigue-PINN: Physics-Informed Fatigue-Driven Motion Modulation and Synthesis

arXiv:2502.19056v2 Announce Type: replace-cross Abstract: Fatigue modeling is essential for motion synthesis tasks to model human motions under fatigued conditions and biomechanical engineering applic

safetyarxiv-cs-lg

Tutorials

Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation

arXiv:2510.10925v2 Announce Type: replace-cross Abstract: Training student models on synthetic data generated by strong teacher models is a promising way to distilling the capabilities of teachers. Ho

tutorialsarxiv-cs-cl

FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer

arXiv:2604.10023v1 Announce Type: cross Abstract: With the growing availability of open-sourced adapters trained on the same diffusion backbone for diverse scenes and objects, combining these pretrain

Applications

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models

arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as

applicationsarxiv-cs-ai

Generation-Augmented Generation: A Plug-and-Play Framework for Private Knowledge Injection in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d

Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models

arXiv:2604.09687v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the i

HearthNet: Edge Multi-Agent Orchestration for Smart Homes

arXiv:2604.09618v1 Announce Type: cross Abstract: Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At

Heterogeneous Consensus-Progressive Reasoning for Efficient Multi-Agent Debate

arXiv:2604.09679v1 Announce Type: cross Abstract: Multi-Agent Debate (MAD) is a collaborative framework in which multiple agents iteratively refine solutions through the generation of reasoning and al

Tutorials

Hierarchical Textual Knowledge for Enhanced Image Clustering

arXiv:2604.11144v1 Announce Type: cross Abstract: Image clustering aims to group images in an unsupervised fashion. Traditional methods focus on knowledge from visual space, making it difficult to dis

tutorialsarxiv-cs-cl

How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities

arXiv:2603.02578v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive domains, yet their unpredictable behaviors, ranging from misalign

Human-AI Interaction Traces as Blackout Poetry: Reframing AI-Supported Writing as Found-Text Creativity

arXiv:2604.09605v1 Announce Type: cross Abstract: LLMs offer new creative possibilities for writers but also raise concerns about authenticity and reader trust, particularly when AI involvement is dis

HyperGraphPro: Progress-Aware Reinforcement Learning for Structure-Guided Hypergraph RAG

arXiv:2601.17755v2 Announce Type: replace Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has emerged as a promising paradigm that organizes external knowledge into structured graphs of enti

safetyarxiv-cs-cl

Latent Structure of Affective Representations in Large Language Models

arXiv:2604.07382v2 Announce Type: replace-cross Abstract: The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implica

Mem^2Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation

arXiv:2604.10923v1 Announce Type: cross Abstract: While large language model--powered agents can self-evolve by accumulating experience or by dynamically creating new assets (i.e., tools or expert age

MERMAID: Memory-Enhanced Retrieval and Reasoning with Multi-Agent Iterative Knowledge Grounding for Veracity Assessment

arXiv:2601.22361v2 Announce Type: replace-cross Abstract: Assessing the veracity of online content has become increasingly critical. Large language models (LLMs) have recently enabled substantial prog

Minimizing classical resources in variational measurement-based quantum computation for generative modeling

arXiv:2604.11578v1 Announce Type: cross Abstract: Measurement-based quantum computation (MBQC) is a framework for quantum information processing in which a computational task is carried out through on

Multi-Granularity Reasoning for Image Quality Assessment via Attribute-Aware Reinforcement Learning to Rank

arXiv:2604.09704v1 Announce Type: new Abstract: Recent advances in reasoning-induced image quality assessment (IQA) have demonstrated the power of reinforcement learning to rank (RL2R) for training vi

Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductions

arXiv:2604.09567v1 Announce Type: cross Abstract: Knowledge representation formalisms are aimed to represent general conceptual information and are typically used in the construction of the knowledge

Tutorials

Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception

arXiv:2604.09886v1 Announce Type: cross Abstract: Accurate volume estimation of objects from visual data is a long-standing challenge in computer vision with significant applications in robotics, logi

tutorialsarxiv-cs-ai

NSFL: A Post-Training Neuro-Symbolic Fuzzy Logic Framework for Boolean Operators in Neural Embeddings

arXiv:2604.10604v1 Announce Type: cross Abstract: Standard dense retrievers lack a native calculus for multi-atom logical constraints. We introduce Neuro-Symbolic Fuzzy Logic (NSFL), a framework that

On the Complexity of the Discussion-based Semantics in Abstraction Argumentation

arXiv:2604.11480v1 Announce Type: new Abstract: We show that deciding whether an argument a is stronger than an argument b with respect to the discussion-based semantics of Amgoud and Ben-Naim is deci

Optimization-Guided Diffusion for Interactive Scene Generation

arXiv:2512.07661v3 Announce Type: replace Abstract: Realistic and diverse multi-agent driving scenes are crucial for evaluating autonomous vehicles, but safety-critical events which are essential for