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Researcher Evidence Record

Arunkumar Byravan

This bounded record lists 21 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.RO, cs.LG, cs.AI work dated 2016 to 2025. The record describes sources and coverage; it makes no judgment about the person.

Compiled coverage vector

Measured lane counts only. Not a trust score or person verdict.

Identity 2 canonical identity row plus typed public identifiers Pith papers 21 attributed paper rows in the Pith corpus, itemized below Imported works 0 imported works beyond the paper ledger Current reviews 3 of 21 papers carrying a current Pith review; presence, not outcome Sourced citations 12 of 21 works with a source-named citation count Coauthors 50 distinct coauthors across shared paper rows
Enumerated paper scope: 4 fields (cs.RO, cs.LG, cs.AI, +1 more) · 2016-2025 sources: authors, author_identifiers · paper_authors · author_works · current_verdicts · cited_works

A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.

Attributed works

A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.

  1. 2025 Pith paper

    Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

    cs.RO provisional current review present

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    16
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: a current Pith review exists.
    Citation counts
    • 44 pith inbound references from cited_work_pith_inbound_counts
  2. 2025 Pith paper

    Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

    cs.CL provisional current review present

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    paper_authors
    Printed name
    Arunkumar Byravan
    Author position
    945
    Identity state
    provisional
    Review coverage
    Measured: a current Pith review exists.
    Citation counts
    • 1032 pith inbound references from cited_work_pith_inbound_counts
  3. 2025 Pith paper

    Gemini Robotics: Bringing AI into the Physical World

    cs.RO provisional current review present

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    paper_authors
    Printed name
    Arunkumar Byravan
    Author position
    15
    Identity state
    provisional
    Review coverage
    Measured: a current Pith review exists.
    Citation counts
    • 116 pith inbound references from cited_work_pith_inbound_counts
  4. 2023 Pith paper

    Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning

    cs.LG provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  5. 2023 Pith paper

    Towards A Unified Agent with Foundation Models

    cs.RO provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  6. 2023 Pith paper

    A Generalist Dynamics Model for Control

    cs.AI provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    8
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 5 pith inbound references from cited_work_pith_inbound_counts
  7. 2023 Pith paper

    Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains

    cs.RO provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  8. 2022 Pith paper

    NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields

    cs.RO provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 2 pith inbound references from cited_work_pith_inbound_counts
  9. 2022 Pith paper

    Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  10. 2022 Pith paper

    The Challenges of Exploration for Offline Reinforcement Learning

    cs.LG provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  11. 2021 Pith paper

    Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes

    cs.RO provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    7
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  12. 2021 Pith paper

    Evaluating model-based planning and planner amortization for continuous control

    cs.RO provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  13. 2021 Pith paper

    Learning Dynamics Models for Model Predictive Agents

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  14. 2021 Pith paper

    On Multi-objective Policy Optimization as a Tool for Reinforcement Learning: Case Studies in Offline RL and Finetuning

    cs.LG provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    8
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 1 pith inbound references from cited_work_pith_inbound_counts
  15. 2020 Pith paper

    Representation Matters: Improving Perception and Exploration for Robotics

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  16. 2020 Pith paper

    Local Search for Policy Iteration in Continuous Control

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    5
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  17. 2019 Pith paper

    Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB

    cs.RO provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    2
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  18. 2019 Pith paper

    Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models

    cs.RO provisional measured, no current review

    paper citation record paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    • 2 pith inbound references from cited_work_pith_inbound_counts
  19. 2019 Pith paper

    Prospection: Interpretable Plans From Language By Predicting the Future

    cs.AI provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  20. 2017 Pith paper

    SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control

    cs.RO provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  21. 2016 Pith paper

    SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks

    cs.LG provisional measured, no current review

    paper paper evidence challenge this paper

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Arunkumar Byravan
    Author position
    1
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.

Evidence apparatus

The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.

LaneStateObservedBoundary and source
identity Measured 2 Canonical identity row plus public typed identifiers.
source=authors, author_identifiers
papers Measured 21 of 21 bounded rows Rows attributed to this author UUID in the Pith corpus.
source=paper_authors
works Measured zero 0 of 0 bounded rows Imported works not duplicated by the paper ledger.
source=author_works
reviews Measured 3 of 21 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured 12 of 21 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 50 of 21 bounded rows Shared-work edges from admitted paper rows.
source=paper_authors
account Unavailable No public count of 1 bounded rows Account metadata is separate from corpus evidence.
source=users.author_id
Public identity sources
  • name variant
    Arunkumar Byravan     backfill
    confidence 0.6

identity history

Enumerated research scope

Fields and dates come only from enumerated, non-disputed Pith paper rows. They do not claim career completeness.

  • cs.RO10 rows
  • cs.LG8 rows
  • cs.AI2 rows
  • cs.CL1 rows
  • 20161 rows
  • 20171 rows
  • 20193 rows
  • 20202 rows
  • 20214 rows
  • 20223 rows
  • 20234 rows
  • 20253 rows
Shared-work index
Record scope

The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.

Paper findings remain attached to papers. They do not become findings about this researcher.