research note
The paper addresses the challenge of efficiently serving coding agents powered by large language models (LLMs), a fast-growing application area for agentic LLMs that engage in multi-step reasoning …
research note
This paper addresses the challenge of integrating uncertainty awareness into generation and decision-making processes of large language models (LLMs) when applied to inherently ambiguous, subjectiv…
research note
UnfoldArt addresses the challenging problem of reconstructing fully articulated 3D objects—including hidden interior geometries—solely from a single image or text input, without requiring supervise…
research note
This paper addresses a critical shortcoming in computer-use (CU) agents: their limited observation interfaces, which currently consist of a single static.
research note
This work studies the emergence of flagellar beating—periodic oscillations resembling biological flagella—in linear chains of magnetic self-propelled.
research note
This paper presents MAM-AI, an on-device medical retrieval-augmented generation (RAG) system designed specifically for nurse-midwives in Zanzibar, where.
research note
This paper proposes Persona-Trained Monte Carlo (PTMC), a novel simulation framework for estimating distributions of financial market outcomes by modeling.
research note
This paper addresses the problem that text-based CAPTCHAs are predominantly designed for English script, posing usability challenges for non-English native speakers, particularly Bengali users
research note
This paper addresses the challenge of evaluating the ethical decision-making behavior of large language models (LLMs) beyond binary right-or-wrong judgments.
research note
This paper addresses the critical challenge of channel-induced distribution shifts in Specific Emitter Identification (SEI) and Specific Emitter Verification (SEV) over wireless fading channels cha…
research note
Democapsid addresses a significant gap in structural virology and biotechnological modeling tools by enabling the generation and visualization of both.
research note
This paper addresses the question of whether an AI agent can autonomously discover useful mathematical theorems from scratch, without relying on any human-provided theorem libraries, training proof…
