norgitov/ trends
Technology · people · ideas
RSS
RUEN
Back to discovery/Daily Papers17 hours ago
ResearchDaily Papers

Learning to Think and Explore in 3D World

We study how vision-language models (VLMs) can learn to think and actively explore in 3D space. Instead of providing multi-view images, videos, or 3D representations to the model, we preserve the native visual encoding of VLMs, i.e., a single image, one at a time, just like humans, and treat the 3D representation only as an environment with which the model can interact through actions (e.g., move left) and observations (rendered images).

Open original
SIGNAL FROM THE SOURCE
65
source votes
Tracking sinceOctober 19, 202665 source votes

This source has not updated recently. Its observation time is shown above.

Momentum—More observations needed
Discussion—Read comments ↗
PublishedOctober 15, 2026Yijiang Li, Bingyang Wang, Nuno Vasconcelos
BEHIND THE NUMBERS

How interest changes

Daily Papers

History starts here

The chart will appear after repeat observations. The current metric comes from the source.

65 source votes

Real observations only. History before source connection is not reconstructed.

WHY IT MAY MATTER

The ACT3D model demonstrates the ability to effectively explore 3D space and improve performance through interaction, which could be useful for applications requiring understanding and navigation in complex environments.

A useful discovery?
KEEP EXPLORING

Connected ideas

Explore topic
Daily Papers

Scene-Designer: Learning Design Intelligence for Agentic 3D Scene Generation

This work introduces Scene-Designer, an agentic framework that learns design intelligence through complementary design and critique experiences. Two datasets, Scene-OTA-35K and Scene-OTC-15K, were created for scene design and quality critique. A Scene-GRPO methodology was proposed to improve design decisions and reduce unnecessary corrections. Experiments demonstrate superior performance in physical validity, functional correctness, and layout coherence.

4 days agoDaily Papers

VLA-Δ: Learning Physical State Transition for Vision-Language-Action Models

Vision-language-action (VLA) models transfer semantic knowledge from vision-language pretraining to robot control, but do not explicitly account for intermediate physical state changes. VLA-Δ uses physical state changes between current and future states as explicit learning targets, with a large-scale pretraining dataset containing annotations of physical state transitions.

5 days agoDaily Papers

Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation

Waypoint-OPD uses an intermediate teacher checkpoint to compare early and late shifts in action preferences during policy transfer. It evaluates the consistency between early and late shifts and suppresses the endpoint shift when they conflict.

5 days agoDaily Papers

Behavioral Compositionality of Sparse Autoencoder Representations

This paper investigates the extent to which sparse autoencoder (SAE) representations support behavioral compositionality. The study introduces SAE Additivity Residuals (SAR) to measure unexplained behavioral variation above a chosen interaction order. Experiments show that learned SAE coordinates exhibit lower first-order residuals compared to random rotations of the same subspace.

5 days agoDaily Papers

RuleTrek: Benchmarking Agentic Rule Reasoning in Complex Scenarios

This paper introduces RuleTrek, a multi-domain benchmark for evaluating agents' ability to reason about rules in complex scenarios. The benchmark uses structured rule graphs and generates sub-scenarios to assess capabilities in rule identification, deduction, and end-to-end reasoning.

6 days agoDaily Papers

Cortex: Consolidating Context into Parametric Memory

Context can enhance the performance of large language models, but these gains may be lost after context removal. Researchers introduced Cortex, which generates prospective queries to anticipate context usage and distills context-conditioned outputs into mergeable low-rank or structural network updates. Cortex shows effectiveness in consolidation and retention of performance.

6 days ago