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STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction

Paper recorded by Signals 4 on 2026-09-30 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.LG · 机器学习 · first seen 2026-10-01

Abstract

Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit promising capabilities such as object recognition, common-sense reasoning, and contextual understanding, capabilities that align with the nuanced requirements of social robot navigation. However, it remains unclear wheth

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#11 most recent of 349 cs.LG papers we have recorded · ↑ newer: OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, · ↓ older: Comparison of techniques for fine-tuning open-weight models for entity
Cite this page: STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction: the #11 most recent of 349 cs.LG papers we have recorded (as of 2026-09-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/stars-from-spatiotemporal-dynamics-to-social-representations-in-human-robot-inte.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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