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Incomplete mobility trajectories can obscure the observations needed to identify important travel events and their endpoints. This study evaluates whether compact, locally deployed large language models (LLMs) can recove...
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Exposure indices that map technical capabilities onto occupational abilities have become a standard tool for anticipating how AI may reshape work, but existing measures either cover software AI or proxy robotics through ...
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Form 10-Q MD&A sections combine long-form management narrative with accounting and forward-looking information. Benchmarks for financial filings commonly evaluate question answering or numerical reasoning, leaving unclea...
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Digital-witnessing research explains how citizen testimony becomes publicly visible. Less is known about audience uptake after publication and whether the attributed source corresponds to the form of response. This study...
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We give a deterministic worst-case algorithm for exact Batched Range Mode on an arbitrary array of length n and a batch of Q intervals. The algorithm returns the mode frequency and the smallest mode identifier for each q...
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Illicit activity in financial networks is difficult to detect. We exploit the idea that the chance of a transaction being illicit depends partly on the concurrent positions and recent actions of counterparties, as well a...
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Computational models have explanatory power to understand cognition in individuals, but there is usually not enough training data to build such models with traditional machine learning. However, alternative architectures...
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Browser agents automate complex workflows by reading and acting on arbitrary page content, but this flexibility exposes them to prompt injection attacks and unintended data exfiltration. Recent work argues that LLM-drive...
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Tabular foundation models (TFMs) are increasingly deployed through black-box APIs and trained on large collections of real-world tabular datasets. As this training paradigm becomes more widely adopted, private or proprie...
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Action-conditioned world models support planning and policy evaluation by predicting future states. However, learning an accurate one-step predictor can require substantial training computation. We introduce Beckmann Wor...
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Large multimodal models (LMMs) are increasingly deployed as agents that perceive, reason, and act in interactive multi-agent environments. Yet most existing benchmarks for LMM-based agents in multi-agent settings remain ...
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Layer 2 (L2) rollups have become the dominant scaling solution in Ethereum. At the core of these systems lies the rollup sequencer, a component that orders, executes, and submits L2 transaction blocks to the main Ethereu...
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Abstract Action-conditioned world models for contact-rich manipulation require data that captures how contact forms, slides, and releases under varying force. Such data are slow to collect through robot teleoperation, wh...
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Text-conditioned 3D human--object interaction (HOI) generation remains challenging because individually plausible human and object motions do not necessarily form a coherent interaction. We argue that a key limitation li...
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Search-augmented language models increasingly serve as long-horizon research agents, yet most open training methods assume a fixed user goal throughout search. We study mid-response steering, where users redirect a model...