SOTAVerified

Zero-shot Generalization

Papers

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Showing 251–275 of 572 papers

TitleStatusHype
DEUX: Active Exploration for Learning Unsupervised Depth Perception—0
DynaPrompt: Dynamic Test-Time Prompt Tuning—0
Temporal-spatial Adaptation of Promptable SAM Enhance Accuracy and Generalizability of cine CMR Segmentation—0
CLIP-PING: Boosting Lightweight Vision-Language Models with Proximus Intrinsic Neighbors Guidance—0
Aether: Geometric-Aware Unified World Modeling—0
Neural Field Dynamics Model for Granular Object Piles Manipulation—0
AoP-SAM: Automation of Prompts for Efficient Segmentation—0
Inference of Affordances and Active Motor Control in Simulated Agents—0
Adversarial Environment Design via Regret-Guided Diffusion Models—0
InCoRo: In-Context Learning for Robotics Control with Feedback Loops—0
In-context Prompt Learning for Test-time Vision Recognition with Frozen Vision-language Model—0
Depth Anything with Any Prior—0
IMRL: Integrating Visual, Physical, Temporal, and Geometric Representations for Enhanced Food Acquisition—0
From Goal-Conditioned to Language-Conditioned Agents via Vision-Language Models—0
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Improving Zero-shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions—0
DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries—0
AnySkin: Plug-and-play Skin Sensing for Robotic Touch—0
Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels—0
Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning—0
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning—0
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas—0
Deep learning universal crater detection using Segment Anything Model (SAM)—0
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology—0
Helping CLIP See Both the Forest and the Trees: A Decomposition and Description Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GR-MGAvg. sequence length4.04—Unverified
2MoDEAvg. sequence length4.01—Unverified
3RoboUniViewAvg. sequence length3.65—Unverified
43D Diffuser ActorAvg. sequence length3.27—Unverified
5GR-1Avg. sequence length3.06—Unverified