Schedule

Suggested Readings:

• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Model Parameters
• Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement
• AgentTuning: Enabling Generalized Agent Abilities for LLMs
• Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents
• 7B Model and 8K Examples: Emerging Reasoning with Reinforcement Learning is Both Effective and Efficient.

Suggested Readings:

• ReAct: Synergizing Reasoning and Acting in Language Models
• Executable Code Actions Elicit Better LLM Agents
• SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
• Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
• SWE-Bench Leaderboard
• Agentless: Demystifying LLM-based Software Engineering Agents
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
• OpenAI Tool Calling
• Micro-agent
• Introducing Gemini 2.0: our new AI model for the agentic era
• Llama 3.3

Suggested Readings:

• Multi-Agent AI Enables Emergent Cognition and Real-Time Knowledge Synthesis in Science and Engineering
• Building effective agents
• StateFlow - Build State-Driven Workflows with Customized Speaker Selection in GroupChat
• Self-Reflective RAG with LangGraph
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
• Multi-Modal RAG
• Evaluate RAG with LlamaIndex
• Evaluating Multi-Modal Retrieval-Augmented Generation
• SWE-Bench
• AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
• ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
• ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
• ToolBench
• Raising the bar on SWE-bench Verified with Claude 3.5 Sonnet
• WebArena

Suggested Readings:

• SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
• BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
• AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation
• FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI
• Measuring Mathematical Problem Solving With the MATH Dataset
• AIME: AI System Optimization via Multiple LLM Evaluators
• AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents

Suggested Readings:

• Towards Trustworthy AI: A Review of Ethical and Robust Large Language Models
• Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
• Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks
• A Survey on Trustworthy LLM Agents: Threats and Countermeasures
• DECODINGTRUST: A Comprehensive Assessment of Trustworthiness in GPT Models
• BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents
• Unveiling Privacy Risks in LLM Agent Memory
• Evil Geniuses: Delving into the Safety of LLM-based Agents
• Extracting Training Data from Large Language Models
• OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning
• StruQ: Defending Against Prompt Injection with Structured Queries
• SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks
• GuardAgent: Safeguard LLM Agents via Knowledge-Enabled Reasoning
• PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action
• A Path for Science and Evidence-based AI Policy