Fireside Index
Last edited: April 4, 2026Below you will find a list of the Fireside articles.
| Article | Date |
|---|---|
| Welcome to the Fireside | |
| Make Models Go Brrr | |
| Todo Lists | |
| “Let’s find time” | |
| Pipes are so bad | |
| Education |
Houjun's Academic Home Page
Last edited: April 4, 2026👋 Howdy, I'm Houjun Liu!
I’m a third-year coterminal MSCS and BSCS student in the Computer Science Department at Stanford University, grateful to be advised by Prof. Mykel Kochenderfer. In the course of my research, I have also had the fortunate opportunity to work with Stanford NLP under Prof. Chris Manning, CMU TalkBank under Prof. Brian MacWhinney, and Prof. Xin Liu at UC Davis Engineering. I am affiliated with the Stanford NLP Group and Stanford Intelligent Systems Lab. I’m also visiting Microsoft Research Frontiers as a research scientist.
EMNLP2025 Index
Last edited: December 12, 2025Talks
- EMNLP2025 Keynote: Heng Ji
- EMNLP2025 Eo: Expert Generalization in MOE
- EMNLP2025 Wu: Zero Shot Graph Learning
- EMNLP2025: MUSE, MCTS Driven Red Teaming
Posters
Takes
- although parsing maybe dead for natural language, structure helps parse scientific information (i.e. drugs, molecules, proteins, etc.)
- two idea: 1) how to formalize approach mathematically 2) what can LMs do that humans can’t do?
- information-rich statefulness + constraints for pruning space is the unlock for ability to build on previous results; i.e. “critical thinking”
Tasks to Do
- EMNLP2025 Fan: medium is not the message: I wonder if we can remove keyboard based signals from BM25 using this method
- EMNLP2025 Xu: tree of prompting: a bunch of multi-hop retrieval datasets to benchmark for RAG-DOLL
- EMNLP2025 Bai: understanding and leveraging expert specialization of context faithfulness: a good set of retrieval benchmarks
Tasks Can Do
- EMNLP2025 Keynote: Heng Ji: “protein LLM requires early exit to capture dynamical Beauvoir”; what if we Mixture of Depth a protein LM?
- EMNLP2025 Hutson: measuring informative of open and questions: formalize this as a rho– POMDP , or use actual value of information measures with Belman backup
- EMNLP2025 Karamanolakis: interactive machine teaching: use MCTS UCB to pick the next set of constitutions to optimize for
- EMNLP2025 Yu: Long-Context LM Fail in Basic Retrieval: I wonder how thoughtbubbles do on the dataset
- EMNLP2025 Bai: understanding and leveraging expert specialization of context faithfulness: could be interesting using the same freeze/clamping technique for cultural work
- EMNLP2025 Vasu: literature grounded hypothesis generation: maybe could use its same hypothesis generation pipeline for RAG
- EMNLP2025Li: enhancing RAG RESPONSE evaluator: maybe could be useful to use to evaluate edge rewards for RAGDOLL
Algorithms Index
Last edited: December 12, 2025Lectures
Divide and Conquer
Sorting
- merge sort: SU-CS161 SEP252025
- recurrence solving: SU-CS161 SEP302025
- median: SU-CS161 OCT022025
- randomized algos + quicksort: SU-CS161 OCT072025
- linear time sorting: SU-CS161 OCT092025
Data Structures
- red-black trees: SU-CS161 OCT142025
- hashing: SU-CS161 OCT212025
Graphs
- DFS/BFS: SU-CS161 OCT232025
- Strongly connected components: SU-CS161 OCT282025
- Dijikstra: SU-CS161 OCT302025
DP
- bellman-ford and Floyd-Warshall: SU-CS161 NOV112025
- more DP LCS, knapsack, independent set: SU-CS161 NOV132025
Greedy Algorithms
- greedy algorithms: SU-CS161 NOV182025
- MSTs: SU-CS161 NOV202025
Closing
- Max Flows, Min Cuts, and Ford-Fulkerson: SU-CS161 DEC022025
ACL2025 Index
Last edited: August 8, 2025Talks
Posters
Takes
- mayhaps we can apply thoughtbubbbles intutiton to BLT token pruning?