#survey
- 19 May 2026 · Paper summary
Paper summary: Code as Agent Harness
A survey that treats code as the infrastructure of agents, not just their output: the interface agents act through, the mechanism for planning, memory and verification, and the shared artefact that coordinates multiple agents.
- 27 Jan 2026 · Paper summary
Paper summary: Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs
A survey of using LLMs to prepare application-ready data: cleaning, integration and enrichment, moving from rule-based pipelines to prompt-driven and agentic workflows.
- 22 Jan 2026 · Paper summary
Paper summary: A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents
A survey organising agentic reasoning into three layers (foundational single-agent skills, self-evolving agents, collective multi-agent reasoning), each split into in-context and post-training approaches.
- 2 Dec 2025 · Paper summary
Paper summary: From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence
A large survey and practical guide to code LLMs, from data curation and pre-training through SFT, RL and coding agents, comparing general and code-specialised models and the gap between benchmarks and real development.
- 18 Jul 2025 · Paper summary
Paper summary: A Survey of Context Engineering for Large Language Models
A survey of over 1,400 papers that defines "context engineering": retrieving, processing and managing everything put into an LLM's context, and how RAG, memory, tools and multi-agent systems build on it.
- 4 Apr 2025 · Paper summary
Paper summary: Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
A book-length survey that frames LLM agents through brain-inspired modules (memory, world model, reward, goals, emotion), then covers self-improvement, multi-agent systems and agent safety.
- 10 Sept 2024 · Paper summary
Paper summary: Towards a Unified View of Preference Learning for Large Language Models: A Survey
A survey that breaks every LLM preference-alignment method into four components, model, data, feedback and algorithm, to show how RLHF, DPO and their relatives connect.
- 28 May 2024 · Paper summary
Paper summary: An Introduction to Vision-Language Modeling
A tutorial-style introduction to vision-language models from a large group of authors: what VLMs are, the main training families, how to train and evaluate them, and the move to video.