Core AI
Large Language Models
Deep dives into GPT, Claude, Gemini, Llama and the transformers powering modern AI
Skills in this topic
5 skills — Sign in to track your progress
LLM Foundations
beginner
Explain how transformers generate text
Prompt Craft
beginner
Write zero-shot and few-shot prompts
LLM Engineering
intermediate
Call LLM APIs with function/tool use
Fine-tuning LLMs
advanced
Prepare fine-tuning datasets
Multimodal LLMs
advanced
Use GPT-4V / Claude Vision for image understanding
Showing 5,326 reads from curated sources
ArXiv cs.AI
🧠 Large Language Models
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⚡ AI Lesson
1mo ago
When Is Collective Intelligence a Lottery? Multi-Agent Scaling Laws for Memetic Drift in LLMs
arXiv:2603.24676v1 Announce Type: new Abstract: Multi-agent systems powered by large language models (LLMs) are increasingly deployed in settings that shape con
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
AutoSAM: an Agentic Framework for Automating Input File Generation for the SAM Code with Multi-Modal Retrieval-Augmented Generation
arXiv:2603.24736v1 Announce Type: new Abstract: In the design and safety analysis of advanced reactor systems, constructing input files for system-level thermal
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Trust as Monitoring: Evolutionary Dynamics of User Trust and AI Developer Behaviour
arXiv:2603.24742v1 Announce Type: new Abstract: AI safety is an increasingly urgent concern as the capabilities and adoption of AI systems grow. Existing evolut
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach
arXiv:2603.24747v1 Announce Type: new Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for form
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Supervising Ralph Wiggum: Exploring a Metacognitive Co-Regulation Agentic AI Loop for Engineering Design
arXiv:2603.24768v1 Announce Type: new Abstract: The engineering design research community has studied agentic AI systems that use Large Language Model (LLM) age
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
ReLope: KL-Regularized LoRA Probes for Multimodal LLM Routing
arXiv:2603.24787v1 Announce Type: new Abstract: Routing has emerged as a promising strategy for balancing performance and cost in large language model (LLM) sys
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
SentinelAI: A Multi-Agent Framework for Structuring and Linking NG9-1-1 Emergency Incident Data
arXiv:2603.24856v1 Announce Type: new Abstract: Emergency response systems generate data from many agencies and systems. In practice, correlating and updating t
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
How Far Are Vision-Language Models from Constructing the Real World? A Benchmark for Physical Generative Reasoning
arXiv:2603.24866v1 Announce Type: new Abstract: The physical world is not merely visual; it is governed by rigorous structural and procedural constraints. Yet,
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
On the Foundations of Trustworthy Artificial Intelligence
arXiv:2603.24904v1 Announce Type: new Abstract: We prove that platform-deterministic inference is necessary and sufficient for trustworthy AI. We formalize this
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
arXiv:2603.24929v1 Announce Type: new Abstract: Understanding and quantifying uncertainty in large language model (LLM) outputs is critical for reliable deploym
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol
arXiv:2603.24943v1 Announce Type: new Abstract: This paper introduces \textbf{FinMCP-Bench}, a novel benchmark for evaluating large language models (LLMs) in so
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Shopping with a Platform AI Assistant: Who Adopts, When in the Journey, and What For
arXiv:2603.24947v1 Announce Type: new Abstract: This paper provides some of the first large-scale descriptive evidence on how consumers adopt and use platform-e
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math
arXiv:2603.24961v1 Announce Type: new Abstract: Assessing student handwritten scratchwork is crucial for personalized educational feedback but presents unique c
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems
arXiv:2603.24963v1 Announce Type: new Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, s
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
The Anatomy of Uncertainty in LLMs
arXiv:2603.24967v1 Announce Type: new Abstract: Understanding why a large language model (LLM) is uncertain about the response is important for their reliable d
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Rethinking Failure Attribution in Multi-Agent Systems: A Multi-Perspective Benchmark and Evaluation
arXiv:2603.25001v1 Announce Type: new Abstract: Failure attribution is essential for diagnosing and improving multi-agent systems (MAS), yet existing benchmarks
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
A Public Theory of Distillation Resistance via Constraint-Coupled Reasoning Architectures
arXiv:2603.25022v1 Announce Type: new Abstract: Knowledge distillation, model extraction, and behavior transfer have become central concerns in frontier AI. The
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
From Stateless to Situated: Building a Psychological World for LLM-Based Emotional Support
arXiv:2603.25031v1 Announce Type: new Abstract: In psychological support and emotional companionship scenarios, the core limitation of large language models (LL
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Mechanistically Interpreting Compression in Vision-Language Models
arXiv:2603.25035v1 Announce Type: new Abstract: Compressed vision-language models (VLMs) are widely used to reduce memory and compute costs, making them a suita
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Sparse Visual Thought Circuits in Vision-Language Models
arXiv:2603.25075v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) improve interpretability in multimodal models, but it remains unclear whether SAE fea
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents
arXiv:2603.25097v1 Announce Type: new Abstract: Large Language Model based agents increasingly operate in high stakes, multi turn settings where factual groundi
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
When Sensing Varies with Contexts: Context-as-Transform for Tactile Few-Shot Class-Incremental Learning
arXiv:2603.25115v1 Announce Type: new Abstract: Few-Shot Class-Incremental Learning (FSCIL) can be particularly susceptible to acquisition contexts with only a
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following
arXiv:2603.25133v1 Announce Type: new Abstract: Rubric-based evaluation has become a prevailing paradigm for evaluating instruction following in large language
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
UniAI-GraphRAG: Synergizing Ontology-Guided Extraction, Multi-Dimensional Clustering, and Dual-Channel Fusion for Robust Multi-Hop Reasoning
arXiv:2603.25152v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems face significant challenges in complex reasoning, multi-hop queries
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
arXiv:2603.25158v1 Announce Type: new Abstract: Equipping Large Language Model (LLM) agents with domain-specific skills is critical for tackling complex tasks.
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
The Competence Shadow: Theory and Bounds of AI Assistance in Safety Engineering
arXiv:2603.25197v1 Announce Type: new Abstract: As AI assistants become integrated into safety engineering workflows for Physical AI systems, a critical questio
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Probabilistic Abstract Interpretation on Neural Networks via Grids Approximation
arXiv:2603.25266v1 Announce Type: new Abstract: Probabilistic abstract interpretation is a theory used to extract particular properties of a computer program wh
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
SliderQuant: Accurate Post-Training Quantization for LLMs
arXiv:2603.25284v1 Announce Type: new Abstract: In this paper, we address post-training quantization (PTQ) for large language models (LLMs) from an overlooked p
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Evaluating Language Models for Harmful Manipulation
arXiv:2603.25326v1 Announce Type: new Abstract: Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it ar
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Macroscopic Characteristics of Mixed Traffic Flow with Deep Reinforcement Learning Based Automated and Human-Driven Vehicles
arXiv:2603.25328v1 Announce Type: new Abstract: Automated Vehicle (AV) control in mixed traffic, where AVs coexist with human-driven vehicles, poses significant
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Agentic Trust Coordination for Federated Learning through Adaptive Thresholding and Autonomous Decision Making in Sustainable and Resilient Industrial Networks
arXiv:2603.25334v1 Announce Type: new Abstract: Distributed intelligence in industrial networks increasingly integrates sensing, communication, and computation
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
4OPS: Structural Difficulty Modeling in Integer Arithmetic Puzzles
arXiv:2603.25356v1 Announce Type: new Abstract: Arithmetic puzzle games provide a controlled setting for studying difficulty in mathematical reasoning tasks, a
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models
arXiv:2603.25412v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on explicit chain-of-thought (CoT) reasoning to solve complex tas
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation
arXiv:2603.25415v1 Announce Type: new Abstract: Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond pure
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Cross-Model Disagreement as a Label-Free Correctness Signal
arXiv:2603.25450v1 Announce Type: new Abstract: Detecting when a language model is wrong without ground truth labels is a fundamental challenge for safe deploym
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Retraining as Approximate Bayesian Inference
arXiv:2603.25480v1 Announce Type: new Abstract: Model retraining is usually treated as an ongoing maintenance task. But as Harrison Katz now argues, retraining
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
EcoThink: A Green Adaptive Inference Framework for Sustainable and Accessible Agents
arXiv:2603.25498v1 Announce Type: new Abstract: As the Web transitions from static retrieval to generative interaction, the escalating environmental footprint o
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Is Mathematical Problem-Solving Expertise in Large Language Models Associated with Assessment Performance?
arXiv:2603.25633v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in math education not only as problem solvers but also as ass
ArXiv cs.AI
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1mo ago
R-C2: Cycle-Consistent Reinforcement Learning Improves Multimodal Reasoning
arXiv:2603.25720v1 Announce Type: new Abstract: Robust perception and reasoning require consistency across sensory modalities. Yet current multimodal models oft
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Back to Basics: Revisiting ASR in the Age of Voice Agents
arXiv:2603.25727v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems have achieved near-human accuracy on curated benchmarks, yet still fa
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
History of generative Artificial Intelligence (AI) chatbots: past, present, and future development
arXiv:2402.05122v1 Announce Type: cross Abstract: This research provides an in-depth comprehensive review of the progress of chatbot technology over time, from
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Malicious LLM-Based Conversational AI Makes Users Reveal Personal Information
arXiv:2506.11680v1 Announce Type: cross Abstract: LLM-based Conversational AIs (CAIs), also known as GenAI chatbots, like ChatGPT, are increasingly used across
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Model2Kernel: Model-Aware Symbolic Execution For Safe CUDA Kernels
arXiv:2603.24595v1 Announce Type: cross Abstract: The widespread adoption of large language models (LLMs) has made GPU-accelerated inference a critical part of
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
X-OPD: Cross-Modal On-Policy Distillation for Capability Alignment in Speech LLMs
arXiv:2603.24596v1 Announce Type: cross Abstract: While the shift from cascaded dialogue systems to end-to-end (E2E) speech Large Language Models (LLMs) improve
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
A Learnable SIM Paradigm: Fundamentals, Training Techniques, and Applications
arXiv:2603.24599v1 Announce Type: cross Abstract: Stacked intelligent metasurfaces (SIMs) represent a breakthrough in wireless hardware by comprising multilayer
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
FED-HARGPT: A Hybrid Centralized-Federated Approach of a Transformer-based Architecture for Human Context Recognition
arXiv:2603.24601v1 Announce Type: cross Abstract: The study explores a hybrid centralized-federated approach for Human Activity Recognition (HAR) using a Transf
ArXiv cs.AI
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1mo ago
MuViS: Multimodal Virtual Sensing Benchmark
arXiv:2603.24602v1 Announce Type: cross Abstract: Virtual sensing aims to infer hard-to-measure quantities from accessible measurements and is central to percep
ArXiv cs.AI
🧠 Large Language Models
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1mo ago
Causal AI For AMS Circuit Design: Interpretable Parameter Effects Analysis
arXiv:2603.24618v1 Announce Type: cross Abstract: Analog-mixed-signal (AMS) circuits are highly non-linear and operate on continuous real-world signals, making
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