arXiv:2210.10278v2 Announce Type: replace-cross Abstract: We study reserve price optimization in multi-phase second price auctions, where the seller’s prior actions affect the bidders’ later valuations through a Markov Decision Process (MDP). Compared to the bandit setting in existing works, the setting in ours involves three challenges. First, from the seller’s perspective, we need to efficiently explore the environment in the presence of potentially untruthful bidders who aim to manipulate the seller’s policy. Second, we want to minimize the […]

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arXiv:2603.28917v1 Announce Type: cross Abstract: This work uncovers variational principles behind symmetrizing the Bregman divergences induced by generic mirror maps over the cone of positive definite matrices. We show that computing the canonical means for this symmetrization can be posed as minimizing the desired symmetrized divergences over a set of mean functionals defined axiomatically to satisfy certain properties. For the forward symmetrization, we prove that the arithmetic mean over the primal space is canonical for any mirror map […]

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I’ve never been good at shell scripting. I’d much rather write scripts in a general purpose language like Python. But occasionally a shell script can do something so simply that it’s worth writing a shell script. Sometimes a shell scripting feature is terse and cryptic precisely because it solves a common problem succinctly. One example of this is working with file extensions. For example, maybe you have a script that takes a source file name like foo.java and […]

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arXiv:2602.11244v1 Announce Type: new Abstract: This work investigates a fundamental question: Do Video-Language Models (VidLMs) robustly account for video content, temporal sequence, and motion? Our investigation shows that, surprisingly, they often do not. We introduce REVEAL{}, a diagnostic benchmark that probes fundamental weaknesses of contemporary VidLMs through five controlled stress tests; assessing temporal expectation bias, reliance on language-only shortcuts, video sycophancy, camera motion sensitivity, and robustness to spatiotemporal occlusion. We test leading open- and closed-source VidLMs and find […]

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We develop emph{Semantic Thermodynamics}, an information-theoretic framework for analyzing hallucinations in transformer systems under finite resources. The central object is mutual information between latent facts and model outputs, together with Fano-style lower bounds on semantic error. We clarify the stochastic assumptions required for non-degenerate information measures, distinguish true data-generating uncertainty from model-implied uncertainty, and replace unsupported hard capacity formulas with explicit capacity surrogates tied to precision, context budget, and effective representational rank. Under standard identification assumptions, we derive […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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Spent ~2 days implementing this paper: TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate Repo: github.com/yashkc2025/turboquant Most quantization stuff I’ve worked with usually falls into one of these: you need calibration data (k-means, clipping ranges, etc.) or you go naive (uniform quant) and take the quality hit This paper basically says: what if we just… don’t do either? The main idea is weirdly simple: take your vector hit it with a random rotation now suddenly the coordinates behave […]

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arXiv:2602.23500v1 Announce Type: new Abstract: Virtual environments (VEs) are increasingly used for immersive experiences, training simulations, and entertainment, yet factors such as height perception and user stance can significantly influence user experience (UX). Height perception in VEs plays a crucial role in shaping UX, particularly in immersive applications such as climbing simulations. This study investigates the effects of height in various VEs and examines how user stance, sitting or standing, impacts immersion, perceived height, and motion sickness. A […]

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arXiv:2601.03385v1 Announce Type: new Abstract: The rapid adoption of synthetic data for training Large Language Models (LLMs) has introduced the technical challenge of “model collapse”-a degenerative process where recursive training on model-generated content leads to a contraction of distributional variance and representational quality. While the phenomenology of collapse is increasingly evident, rigorous methods to quantify and predict its onset in high-dimensional spaces remain elusive. In this paper, we introduce SIGMA (Spectral Inequalities for Gram Matrix Analysis), a unified […]

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