llmducation

Staying up to date with Large Language Models (no hype).

This is my plan for staying excited about large language models:

1. Stop worrying about missing the latest trendy python framework.

2. Make a reading list which covers all of the important LLM innovations (both academia and industry) and work through the list. I want the list to contain both papers (academia) and commentary on (successful) practical applications of LLMs.

3. Subscribe to email newsletters, LinkedIn, YouTube and Twitter accounts of significant LLM innovators and commentators (avoiding sources focusing on hype and speculation).

Here is my (constantly evolving) reading list:

Status	Title	Value	Year	Topic	Type	Notes	Link(s)
✅ read	ReAct: Synergizing Reasoning and Acting in Language Models	★★★★★	2023	LLM Prompting	paper	Compelling and readable	https://arxiv.org/abs/2210.03629
✅ read	Self-consistency improves chain of thought reasoning in language models	★★★★☆	2022	LLM Prompting	paper		https://arxiv.org/abs/2203.11171
✅ read	Hermes: A Text-to-SQL solution at Swiggy	★★★★★			blog		https://bytes.swiggy.com/hermes-a-text-to-sql-solution-at-swiggy-81573fb4fb6e
✅ read	A survey on large language model based autonomous agents	★★★★★	2024		paper		https://link.springer.com/article/10.1007/s11704-024-40231-1
✅ read	Reflexion: Language Agents with Verbal Reinforcement Learning	★★★★★	2023	LLM Agents	paper	Simple but very powerful concept	https://arxiv.org/abs/2303.11366
✅ read	RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation	★★★★★	2024	LLM Evaluation	paper	very convincing and elegant framework. Very thorough research	https://arxiv.org/abs/2408.08067
✅ read	RefChecker: Reference-based Fine-grained Hallucination Checker and Benchmark for Large Language Models		2024	LLM Evaluation	paper	this framework is also used in the RAGChecker paper	https://arxiv.org/abs/2405.14486
✅ read	Cognitive Architectures for Language Agents	★★★★★	2023	LLM Agents	paper	notes	https://arxiv.org/abs/2309.02427
✅ read	Scaling Test Time Compute with Open Models	★★★★★	2024	Test Time Compute	blog	Much more readable than the original paper	https://huggingface.co/spaces/HuggingFaceH4/blogpost-scaling-test-time-compute
✅ read	Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration	★★★★★	2024	reasoning	paper	I loved this paper! Such a straightforward but creative concept	https://arxiv.org/abs/2307.05300
❌ not started	KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation		2024	RAG	paper
✅ read	Reasoning over Uncertain Text by Generative Large Language Models	★★★☆☆	2024		paper	Less applied than I'd hoped (more theoretical) but still quite interesting	https://arxiv.org/abs/2402.09614v3
❌ not started	Understanding Multimodal LLMs		2024	Multi-Modal LLMs	blog	notes	https://www.linkedin.com/pulse/understanding-multimodal-llms-sebastian-raschka-phd-t7h5c
❌ not started	Large Language Models Understand and Can Be Enhanced by Emotional Stimuli		2023	LLM Prompting	paper
❌ not started	The Llama 3 Herd of Models		2024	Foundation models	paper
◐ partially read	Build a Large Language Model (from scratch)	★★★★★		LLM Architecture	book	If I could read only 1 thing, this would be it
✅ read	Orchestrating Agents: Routines and Handoffs	★★★★☆	2024	LLM Agents	blog	Very clear. Nice python code examples with no additional frameworks required	https://cookbook.openai.com/examples/orchestrating_agents
✅ read	Endless Jailbreaks with Bijection Learning	★★★★★	2024	LLM Security	paper	very simple but powerful technique	https://arxiv.org/abs/2410.01294
✅ read	Multi-expert Prompting Improves Reliability, Safety, and Usefulness of Large Language Models	★★★★☆	2024		paper	Very novel, effective and interpretable technique	https://arxiv.org/abs/2411.00492
◐ partially read	Fine-tuning Embedding Models for RAG	★★★★★	2024	Embeddings	blog	Impressive performance gain. Contains lots of useful code	https://www.philschmid.de/fine-tune-embedding-model-for-rag
◐ partially read	Graph Retrieval-Augmented Generation: A Survey	★★★☆☆	2024	RAG	paper	notes	https://arxiv.org/abs/2408.08921
❌ not started	Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack		2024	LLM Security	paper		https://arxiv.org/abs/2404.01833
✅ read	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	★★★★☆	2018	Foundation Models	paper		https://arxiv.org/abs/1810.04805
❌ not started	Chain-of-Thought Reasoning Without Prompting		year	topic	type	notes	https://arxiv.org/abs/2402.10200
✅ read	o1 isn't a chat model (and that's the point)	★★★★☆	2025	Test-time compute	blog		https://www.latent.space/p/o1-skill-issue
❌ not started	Tree of Thoughts: Deliberate Problem Solving with Large Language Models	★★☆☆☆	year	topic	type	notes	https://arxiv.org/abs/2305.10601
❌ not started	Graph of Thoughts: Solving Elaborate Problems with Large Language Models		2023	LLM Agents	paper	notes	https://arxiv.org/abs/2308.09687
❌ not started	GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models		2024	LLM Limitations	paper		https://arxiv.org/abs/2410.05229v1
❌ not started	From Local to Global: A Graph RAG Approach to Query-Focused Summarization		2024	RAG	paper	notes	links
◐ partially read	What We've Learned From a Year of Building with LLMs		2024	llm-ops	blog		https://applied-llms.org
❌ not started	Large Language Models are Zero-Shot Reasoners		2022	LLM Prompting	paper	notes	https://arxiv.org/abs/2205.11916
❌ not started	Planning with Large Language Models via Corrective Re-prompting		2022	topic	paper	notes	https://openreview.net/pdf?id=cMDMRBe1TKs
❌ not started	Evaluating and enhancing probabilistic reasoning in language models		2024		blog	notes	https://research.google/blog/evaluating-and-enhancing-probabilistic-reasoning-in-language-models/
❌ not started	ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models		2023	LLM Agents	paper	notes	https://arxiv.org/abs/2305.18323
❌ not started	Sparse Priming Representations		2023		github repo		https://github.com/daveshap/SparsePrimingRepresentations https://www.youtube.com/watch?v=YjdmYCd6y0M
❌ not started	BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents		2023	LLM Agents	paper		https://arxiv.org/abs/2308.05960 https://github.com/salesforce/BOLAA
◐ partially read	ML and LLM system design: 450 case studies to learn from	★★★★★	2024	llm-ops	website	notes	https://www.evidentlyai.com/ml-system-design
❌ not started	Your RAG application is a communication system		2024	RAG	blog	notes	https://superlinked.com/vectorhub/articles/rag-application-communication-system
❌ not started	Reader-LM: Small Language Models for Cleaning and Converting HTML to Markdown		2024		blog	notes	https://jina.ai/news/reader-lm-small-language-models-for-cleaning-and-converting-html-to-markdown/
❌ not started	Writing in the Margins: Better Inference Pattern for Long Context Retrieval		2024	RAG	paper	notes	https://www.arxiv.org/abs/2408.14906
❌ not started	Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters		2024		paper	notes	https://arxiv.org/abs/2408.03314
❌ not started	LightRAG: Simple and Fast Retrieval-Augmented Generation		2024	RAG	paper	notes	https://arxiv.org/abs/2410.05779
❌ not started	GPT-4 Technical Report		2024	LLM Architecture	paper	notes	https://arxiv.org/abs/2303.08774
❌ not started	Sparks of Artificial General Intelligence: Early experiments with GPT-4		2023	AGI	paper	notes	https://arxiv.org/abs/2303.12712
❌ not started	A Survey of Large Language Models		ongoing (started 2023)		paper (survey)	notes	https://arxiv.org/abs/2303.18223
❌ not started	QLoRA: Efficient Finetuning of Quantized LLMs		2023	Quantization	paper	notes	https://arxiv.org/abs/2305.14314
❌ not started	Mamba: Linear-Time Sequence Modeling with Selective State Spaces		2024	LLM Architecture	paper	notes	https://arxiv.org/abs/2312.00752
❌ not started	Towards Expert-Level Medical Question Answering with Large Language Models		2023		paper	notes	https://arxiv.org/abs/2305.09617
❌ not started	ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question Answering		2024	RAG	paper	notes	https://arxiv.org/abs/2410.05077
◐ partially read	Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization		2024	LLM Persona	paper (survey)		https://arxiv.org/abs/2406.01171
◐ partially read	Quantifying the Persona Effect in LLM Simulations		2024	LLM Persona	paper	notes	https://arxiv.org/abs/2402.10811
❌ not started	Looking Inward: Language Models Can Learn About Themselves by Introspection		2024		paper	notes	https://arxiv.org/abs/2410.13787
❌ not started	Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences		2024	LLM Evaluation	paper	notes	https://arxiv.org/abs/2404.12272
✅❌templaterow	title	★★☆☆☆	year	topic	type	notes	links

Also to check out:

• https://magazine.sebastianraschka.com/p/llm-research-papers-the-2024-list
• SmolLM2
• (paper) Efficient Few-Shot Learning Without Prompts

LLM sampling techniques:

• temperature sampling (Ackley et al., 1985; Ficler & Goldberg, 2017)

• top-k sampling (Fan et al., 2018; Holtzman et al., 2018; Radford et al., 2019)

• nucleus sampling (Holtzman et al., 2020)

Subscribed to/followed:

• Data Elixir

• Andrej Karpathy

• Sebastian Raschka

• AI Tidbits

• AlphaSignal

• Data Science Weekly

• The Batch (Andrew NG)

Interesting projects:

Project Name	Description	Link(s)
optillm		<https://github.com/codelion/optillm

References and Resources:

• https://www.zeta-alpha.com/post/analyzing-the-homerun-year-for-llms-the-top-100-most-cited-ai-papers-in-2023-with-all-medals-for-o

• Anti-hype LLM reading list (github repo)

• LLM Agents Papers (github repo)