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researcher

João F. Henriques

4 papers hereh-index 269 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • cs.LG1
  • cs.RO1
same name
  • João F. Henriques — 23 papers, h 31
  • João F. Henriques — 5 papers, h 1
  • João F. Henriques — 4 papers, h 2
  • João F. Henriques — 4 papers, h 2
  • João F. Henriques — 4 papers, h 2
  • João F. Henriques — 3 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedVisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning

3 citations · 3 across the 3 of their papers we have counts for

collaborators

4 papers

cs.AI2026

AI Research Preference Models

Thomas Simon Foster, Bassel Al Omari, Tingchen Fu +30

AI research agents (AIRA) can now carry machine learning experiments from proposal through implementation and evaluation. Yet progress on frontier tasks is throttled by the cost of…

cs.LG2026

Finding the Time to Think: Learning Planning Budgets in Real-Time RL

Aneesh Muppidi, Firas Darwish, Dylan Cope +2

Deliberating takes time. In real-time settings, that time is not free. Standard reinforcement learning (RL) sidesteps this as the environment waits indefinitely for the agent's dec…

cs.AI2024★ 3 cited

VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning

Yichao Liang, Nishanth Kumar, Hao Tang +5

Broadly intelligent agents should form task-specific abstractions that selectively expose the essential elements of a task, while abstracting away the complexity of the raw sensori…

cs.RO2023

Rapid Motor Adaptation for Robotic Manipulator Arms

Yichao Liang, Kevin Ellis, João Henriques

Developing generalizable manipulation skills is a core challenge in embodied AI. This includes generalization across diverse task configurations, encompassing variations in object…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.