You are very much ON TIME
Record a decent little poem that I saw~
Reading Notes of DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference
Last layer hidden state already has information related to uncertainty.
Reading Notes of SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
Train a smaller model to predict what lines to be deleted for the read action of coding agent. The pruned part is sent back to the agent. The training pipeline is not clear.
Reading Notes of SideQuest: Model-Driven KV Cache Management for Long-Horizon Agentic Reasoning
Train an agent to spawn an auxiliary agent from the ongoing trajectory to select blocks of KV cache from history and delete at regular intervals.
Simulation Modeling
My class notes on simulation modeling, based on the textbook Simulation Modeling and Analysis (Averill M. Law, 5th edition, McGraw-Hill).
1. Discrete Event Simulation
What a discrete-event simulation consists of — entities, events, the event list, the clock, and statistical counters — walked through on a single-server FCFS queue.
2. Review of Probability and Statistics
A recap of the probability and statistics needed for simulation: probability axioms, random variables, convergence modes, stochastic processes, and estimation of means and variances.
3. Random Number Generation
Every random variate in a simulation is built from i.i.d. U(0,1) numbers; these notes cover where those numbers come from and what makes a generator good.
