Skip to content
Papers.

Recurrent-Depth VLA: Implicit Test-Time Compute Scaling of Vision-Language-Action Models via Latent Iterative Reasoning research paper by Ai2, 2026

Ai2 · Feb 8, 2026 · Reasoning · 16 citations · 71 upvotes · unverified

Read on arXiv

What it shows

RD-VLA introduces a recurrent architecture for vision-language-action models that adapts computational depth through latent iterative refinement, achieving constant memory usage and improved task success rates.

UnverifiedHugging Face's summary; not yet checked by hand.

More from Ai2

All 7
PaperCitations
MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction3D point motion forecasting model predicts object trajectories from visual history and language goals, demonstrating superior performance on benchmarks and transferring effectively to robot manipulation and video generation tasks.Multimodal and robotics · Jun 2026 · Unverified4
MolmoAct2: Action Reasoning Models for Real-world DeploymentA fully open robot action model, released with new datasets including 720 hours of two-arm teleoperation.Multimodal and robotics · May 202644
WildDet3D: Scaling Promptable 3D Detection in the WildA unified 3D object detection framework with a large-scale dataset enables open-world detection with multiple prompt types and geometric cue integration.Multimodal and robotics · Apr 2026 · Unverified11
TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for RoboticsTOPReward is a probabilistically grounded temporal value function that uses pretrained video Vision-Language Models to estimate robotic task progress through internal token logits, achieving superior performance in zero-shot evaluations across diverse real-world tasks.Inference and efficiency · Feb 2026 · Unverified28
Olmo 3Olmo 3, a family of state-of-the-art fully-open language models at 7B and 32B parameter scales, excels in long-context reasoning, function calling, coding, instruction following, general chat, and knowledge recall.Reasoning · Dec 2025 · Unverified0
MolmoAct: Action Reasoning Models that can Reason in SpaceAction Reasoning Models (ARMs) integrate perception, planning, and control to enable adaptable and explainable robotic behavior, achieving superior performance across various tasks and settings.Reasoning · Aug 2025 · Unverified185

Other reasoning papers

Topic
PaperCitations
Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsAsking a model to write out its intermediate steps (chain of thought) sharply improves its math and logic answers.Google · Jan 202222.1k
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsDeepSeekMath 7B improves mathematical reasoning through enhanced data pre-training and Group Relative Policy Optimization, achieving high scores on MATH benchmark without external tools.DeepSeek · Feb 2024 · Unverified8,994
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningReinforcement learning taught a model long step-by-step reasoning on par with OpenAI o1.DeepSeek · Jan 20255,694
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligenceDeepSeek-Coder-V2, a Mixture-of-Experts language model, excels in code-specific tasks by enhancing coding and mathematical reasoning capabilities while expanding language support and context length.DeepSeek · Jun 2024 · Unverified502
ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent PlanningThinkAct, a dual-system framework, uses reinforced visual latent planning to enable few-shot adaptation, long-horizon planning, and self-correction in embodied AI tasks by bridging high-level reasoning with low-level action execution.NVIDIA · Jul 2025 · Unverified172
WebShaper: Agentically Data Synthesizing via Information-Seeking FormalizationWebShaper, a formalization-driven framework, synthesizes information-seeking datasets using set theory and Knowledge Projections to enhance reasoning structure and achieve top performance in open-sourced benchmarks.Alibaba (Qwen) · Jul 2025 · Unverified113
About this paper
Authors
Yalcin Tur, Jalal Naghiyev, Haoquan Fang and 4 more
arXiv
2602.07845 · PDF
Venue
arXiv.org
Citations
16, 1 influential · Semantic Scholar
Upvotes
71 · Hugging Face
Code
github.com/rd-vla/rd-vla
Lab
Ai2 · on Companies

Changes

What changed
Influential citationsfirst count: 1Sep 25, 2026
Citationsfirst count: 16Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

New papers by email

Monday afternoons, only in weeks with new papers from the labs.

Double opt-in. Unsubscribe any time.