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All ⚡ AI Lessons (5486) ArXiv cs.AIOpenAI NewsForbes InnovationHugging Face BlogDev.to AIHackernoon
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
The Collaboration Paradox: Why Generative AI Requires Both Strategic Intelligence and Operational Stability in Supply Chain Management
arXiv:2508.13942v2 Announce Type: replace Abstract: The rise of autonomous, AI-driven agents in economic settings raises critical questions about their emergent
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
From Guidelines to Guarantees: A Graph-Based Evaluation Harness for Domain-Specific Evaluation of LLMs
arXiv:2508.20810v2 Announce Type: replace Abstract: Rigorous evaluation of domain-specific language models requires benchmarks that are comprehensive, contamina
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
GeoSketch: A Neural-Symbolic Approach to Geometric Multimodal Reasoning with Auxiliary Line Construction and Affine Transformation
arXiv:2509.22460v3 Announce Type: replace Abstract: Geometric Problem Solving (GPS) poses a unique challenge for Multimodal Large Language Models (MLLMs), requi
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
SAG-Agent: Enabling Long-Horizon Reasoning in Strategy Games via Dynamic Knowledge Graphs
arXiv:2510.15259v3 Announce Type: replace Abstract: Most commodity software lacks accessible Application Programming Interfaces (APIs), requiring autonomous age
ArXiv cs.AI 📄 Paper ⚡ AI Lesson 1w ago
CastMind: An Interaction-Driven Agentic Reasoning Framework for Cognition-Inspired Time Series Forecasting
arXiv:2511.08947v3 Announce Type: replace Abstract: Time series forecasting plays a crucial role in decision-making across many real-world applications. Despite
ArXiv cs.AI 📄 Paper ⚡ AI Lesson 1w ago
Pharos-ESG: A Framework for Multimodal Parsing, Contextual Narration, and Hierarchical Labeling of ESG Report
arXiv:2511.16417v2 Announce Type: replace Abstract: Environmental, Social, and Governance (ESG) principles are reshaping the foundations of global financial gov
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
arXiv:2512.16917v3 Announce Type: replace Abstract: Large language models (LLMs) with explicit reasoning capabilities excel at mathematical reasoning yet still
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering
arXiv:2601.10402v5 Announce Type: replace Abstract: The advancement of artificial intelligence toward agentic science is currently bottlenecked by the challenge
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Are LLMs Smarter Than Chimpanzees? An Evaluation on Perspective Taking and Knowledge State Estimation
arXiv:2601.12410v2 Announce Type: replace Abstract: Cognitive anthropology suggests that the distinction of human intelligence lies in the ability to infer othe
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
CollectiveKV: Decoupling and Sharing Collaborative Information in Sequential Recommendation
arXiv:2601.19178v2 Announce Type: replace Abstract: Sequential recommendation models are widely used in applications, yet they face stringent latency requiremen
ArXiv cs.AI 📄 Paper ⚡ AI Lesson 1w ago
CIRCLE: A Framework for Evaluating AI from a Real-World Lens
arXiv:2602.24055v4 Announce Type: replace Abstract: This paper proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-c
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Agentified Assessment of Logical Reasoning Agents
arXiv:2603.02788v3 Announce Type: replace Abstract: We present a framework for evaluating and benchmarking logical reasoning agents when assessment itself must
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learning
arXiv:2603.03072v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist scientists across diverse workflows. A key chal
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
GPT4o-Receipt: A Dataset and Human Study for AI-Generated Document Forensics
arXiv:2603.11442v2 Announce Type: replace Abstract: Can humans detect AI-generated financial documents better than machines? We present GPT4o-Receipt, a benchma
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Relationship-Aware Safety Unlearning for Multimodal LLMs
arXiv:2603.14185v3 Announce Type: replace Abstract: Generative multimodal models can exhibit safety failures that are inherently relational: two benign concepts
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
DomAgent: Leveraging Knowledge Graphs and Case-Based Reasoning for Domain-Specific Code Generation
arXiv:2603.21430v2 Announce Type: replace Abstract: Large language models (LLMs) have shown impressive capabilities in code generation. However, because most LL
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
Human strategic decision making in parametrized games
arXiv:2104.14744v5 Announce Type: replace-cross Abstract: Many real-world games contain parameters which can affect payoffs, action spaces, and information stat
ArXiv cs.AI 📄 Paper ⚡ AI Lesson 1w ago
Entire Space Counterfactual Learning for Reliable Content Recommendations
arXiv:2210.11039v3 Announce Type: replace-cross Abstract: Post-click conversion rate (CVR) estimation is a fundamental task in developing effective recommender
ArXiv cs.AI 🧠 Large Language Models 📄 Paper ⚡ AI Lesson 1w ago
A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data and LLMs Perspective
arXiv:2211.14997v5 Announce Type: replace-cross Abstract: Enterprise financial risk analysis aims at predicting the future financial risk of enterprises. Due to
ArXiv cs.AI 📄 Paper ⚡ AI Lesson 1w ago
Perturbative adaptive importance sampling for Bayesian LOO cross-validation
arXiv:2402.08151v4 Announce Type: replace-cross Abstract: Importance sampling (IS) is an efficient stand-in for model refitting in performing (LOO) cross-valida