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From the 1 of 5 linked papers with an AI index.

collaborators

5 papers

cs.CL2026

In-Place Tokenizer Expansion for Pre-trained LLMs

Jimmy T. H. Smith, Tarek Dakhran, Alberto Cabrera +7

The paper proposes an in‑place tokenizer expansion method that continues a pre‑trained model’s BPE merges on multilingual data, reuses existing token embeddings, and initializes ne…

cs.LG2026

MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

Maksim Kuznetsov, Zulfat Miftahutdinov, Rim Shayakhmetov +17

General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and performance required for drug discovery tasks…

cs.LG2025

Zero-Overhead Introspection for Adaptive Test-Time Compute

Rohin Manvi, Joey Hong, Tim Seyde +3

Large language models excel at reasoning but lack key aspects of introspection, including anticipating their own success and the computation required to achieve it. Humans use real…

cs.LG2025

LFM2 Technical Report

Alexander Amini, Anna Banaszak, Harold Benoit +30

We present LFM2, a family of Liquid Foundation Models designed for efficient on-device deployment and strong task capabilities. Using hardware-in-the-loop architecture search under…

cs.CV2025

Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models

Haoyang Wu, Tsun-Hsuan Wang, Mathias Lechner +7

Surgical workflow analysis is essential in robot-assisted surgeries, yet the long duration of such procedures poses significant challenges for comprehensive video analysis. Recent…