40x less overhead! Rateless Invertible Bloom Filters - Part 3 of 3

One Hash Bloom Filters - Jim Calabro

Jim Calabro

inkandswitch/subduction

🏔️ Sync protocol for hash-linked data

Practical Rateless Set Reconciliation

HTML conversions sometimes display errors due to content that did not convert correctly from the source. This paper uses the following packages that are not yet supported by the HTML conversion tool. Feedback on these issues are not necessary; they are known and are being worked on.

Compiling Match Statements to Bytecode

Full pipeline deep dive for purple garden: AST, BB SSA IR, Bytecode, Optimisations

FlowLog - Efficient and Extensible Datalog | FlowLog

FlowLog: Efficient and Extensible Datalog via Incrementality

An LLM Workflow That Reproduces, Improves, and Extends Published Economics Research

We introduce an open-source workflow that enables an LLM to reproduce, improve, and extend an economics article using the article’s published replication package. First, the workflow attempts to reproduce the original calculations, checks for discrepancies with published findings, and performs automated sensitivity analysis. Across 4,452 published replication packages for five economics journals, the workflow flags discrepancies in 3,460 articles or their appendices. Second, the workflow improves the original calculations by using a different implementation or algorithm. In 496 articles, the workflow is able to reduce a calculation’s computation time, at similar or greater accuracy, by more than a factor of 10. Third, the workflow extends the original analysis. In 923 articles, the workflow develops an extension that does not appear in the original article and that is aligned with the original article’s goals and assumptions.

Email filters: Stay organized with these best practices | Proton

Learn how email filters can create better email organization and workflow, and increase your productivity at work.

Email filters: Stay organized with these best practices | Proton

Learn how email filters can create better email organization and workflow, and increase your productivity at work.

Making Databases Faster with LLM Evolutionary Sampling

Traditional query optimization relies on cost-based optimizers that estimate execution cost (e.g., runtime, memory, and I/O) using predefined heuristics and statistical models. Improving these heuristics requires substantial engineering effort, and even when implemented, these heuristics often cannot take into account semantic correlations in queries and schemas that could enable better physical plans. Using our DBPlanBench harness for the DataFusion engine, we expose the physical plan through a compact serialized representation and let the LLM propose localized edits that can be applied and executed. We then apply an evolutionary search over these edits to refine candidates across iterations. Our key insight is that LLMs can leverage semantic knowledge to identify and apply non-obvious optimizations, such as join orderings that minimize intermediate cardinalities. We obtain up to 4.78$\times$ speedups on some queries and we demonstrate a small-to-large workflow in which optimizations found on small databases transfer effectively to larger databases.

Ante: A New Way to Blend Borrow Checking and Reference Counting

Ante has taken the first step towards something we all thought was impossible: blending reference counting and borrow checking without run-time crashes. 0