Stanford UG Y1, Aut

• Decision Making Index
• Computer Systems Index
• CS Probability Index
• Speech Processing Index

Stanford UG Y1, Win

• ODEs Index
• OS Index
• POMDPs Index
• Language Information Index

Stanford UG Y1, Spr

• Optimization Index
• Rust Systems Index
• Signal Processing Index
• NLP Index
• Democracy Index

Stanford UG Y2, Aut

• PL Index
• Theory of Computing Index

Stanford UG Y2, Win

• Complexity Theory Index
• ML Math Index
• Validation Index

Stanford UG Y2, Spr

• Complexity Theory Index
• Compilers Index
• Moral Philosophy Index

Stanford UG Y3, Aut

• Machine Learning Index
• Algorithms Index

Stanford UG Talks

Contacts

Talk Contacts

SU-CS161 Things to Review

SU-CS161 Embedded Ethics

Lectures

Divide and Conquer

• SU-CS161 SEP232025

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

Talks

• EMNLP2025 Keynote: Heng Ji
• EMNLP2025 Eo: Expert Generalization in MOE
• EMNLP2025 Wu: Zero Shot Graph Learning
• Driven Red Teaming

Posters

• EMNLP2025 Wednesday Morning Posters
• EMNLP2025 Friday Afternoon Posters
• EMNLP2025 Extra Things

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

Talks

• ACL2025 Keynote: Luke Zettemoyer
• ACL2025 Orals: Language Modeling 1
• ACL2025 Orals: QA

Posters

• ACL2025 Monday Morning Posters
• ACL2025 Tuesday Morning Posters
• ACL2025 Tuesday Afternoon Posters

Takes

• mayhaps we can apply thoughtbubbbles intutiton to BLT token pruning?

The ADReSS Literature Survey is a literature survey for the results published during the ADReSS Challenge.

• Antonsson 2021: disfluency + SVF features trained on SVM: lexical > narrative qual.
• Chlasta 2021: features extracted from VGGish on SVM; also trained new CNN from .wav.
• Sadeghian 2021: Used GA for feature sel., achieved 94% w/ MMSE alone; dev’d ASR tool.
• Martinc 2021: CBOW (text) + ADR (sound) late fusion’d to a BERT, ablated for features.
• Meghanani 2021: spontaneous speech transcripts with fastText and CNN; 83.33% acc.
• Yuan 2021: ERNIE on transcripts with pause encoding; 89.6% acc.
• Jonell 2021: Developed a kitchen sink of diag. tools and correlated it with biomarkers.
• Laguarta 2021: multimodel (OVBM) to embed auditory info + biomarkers for clsf.
• Shah 2021: late fusion of n-gram and OpenSMILE on std. classifiers.
• Lindsay 2021: Cross-linguistic markers shared for AD patients between English and French.
• Zhu 2021: late fusion of CTP task for AD clsf. w/ transf., mobilenet, yamnet, mockingjay.
• Guo 2021: WLS data to augment CTP from ADReSS Challenge and trained it on a BERT.
• Balagopalan 2021: lexo. and synt. features trained on a BERT and other models.
• Mahajan 2021: a bimodal model on speech/text with GRU on speech and CNN-LSTM on text.
• Parvin 2020: excercize scheme effects on theta/alpha ratio and Brain wave frequency.
• Luz 2021: review paper presenting the ADReSSo challenge and current baselines.

From Meghanani 2021, a review: