mailitics

Tag: meta

  • Meta Flow Maps enable scalable reward alignment

    Meta Flow Maps enable scalable reward alignment arXiv:2601.14430v1 Announce Type: new Abstract: Controlling generative models is computationally expensive. This is because optimal alignment with a reward function–whether via inference-time steering or fine-tuning–requires estimating the value function. This task demands access to the conditional posterior $p_{1|t}(x_1|x_t)$, the distribution of clean data $x_1$ consistent with an intermediate…

  • Meta’s top AI researchers thinks LLMs are a dead end. Do many people here feel the same way from a technical perspective?

    Meta’s top AI researchers thinks LLMs are a dead end. Do many people here feel the same way from a technical perspective? submitted by /u/sext-scientist [link] [comments] /u/sext-scientist Go to original source

  • Does meta only have product analytics?

    Does meta only have product analytics? I have been told that all meta data scientists are all product analysts meaning that they do ab tests and sql. Despite this, i ve been told by friends of mine that google, amazon, uber… they all have two different types of data scientist: one doing product analytics and…

  • Meta Optimality for Demographic Parity Constrained Regression via Post-Processing

    Meta Optimality for Demographic Parity Constrained Regression via Post-Processing arXiv:2506.13947v1 Announce Type: new Abstract: We address the regression problem under the constraint of demographic parity, a commonly used fairness definition. Recent studies have revealed fair minimax optimal regression algorithms, the most accurate algorithms that adhere to the fairness constraint. However, these analyses are tightly coupled…

  • A Meta-learner for Heterogeneous Effects in Difference-in-Differences

    A Meta-learner for Heterogeneous Effects in Difference-in-Differences arXiv:2502.04699v1 Announce Type: new Abstract: We address the problem of estimating heterogeneous treatment effects in panel data, adopting the popular Difference-in-Differences (DiD) framework under the conditional parallel trends assumption. We propose a novel doubly robust meta-learner for the Conditional Average Treatment Effect on the Treated (CATT), reducing the…

  • Advancing AI Reasoning: Meta-CoT and System 2 Thinking

    Advancing AI Reasoning: Meta-CoT and System 2 Thinking How Meta-CoT enhances system 2 reasoning for complex AI challenges Continue reading on Towards Data Science » Kaushik Rajan Go to original source

  • Is data science at meta just a/b testing?

    Is data science at meta just a/b testing? I’ve been at Meta a year and all I do is run a/b tests. In my old jobs I used to build models and products using data science. Does this happen under a different job title here or am I just in wrong department? submitted by /u/Longjumping-Will-127…