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Zero-shot Generalization

Papers

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Showing 351–375 of 572 papers

TitleStatusHype
A Simple yet Efficient Ensemble Approach for AI-generated Text Detection—0
Octavius: Mitigating Task Interference in MLLMs via LoRA-MoECode0
What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction TuningCode1
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization—0
Neural Field Dynamics Model for Granular Object Piles Manipulation—0
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy InstructionsCode1
Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive TasksCode1
ZGUL: Zero-shot Generalization to Unseen Languages using Multi-source Ensembling of Language AdaptersCode0
Matryoshka Diffusion ModelsCode2
Robot Skill Generalization via Keypoint Integrated Soft Actor-Critic Gaussian Mixture Models—0
Lag-Llama: Towards Foundation Models for Probabilistic Time Series ForecastingCode3
What Matters to You? Towards Visual Representation Alignment for Robot Learning—0
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining—0
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language ModelsCode0
On the Zero-Shot Generalization of Machine-Generated Text Detectors—0
On the Performance of Multimodal Language Models—0
PACIT: Unlocking the Power of Examples for Better In-Context Instruction TuningCode0
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement LearningCode1
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for EchocardiographyCode1
BELT:Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision—0
Light Field Diffusion for Single-View Novel View Synthesis—0
DEUX: Active Exploration for Learning Unsupervised Depth Perception—0
DePT: Decoupled Prompt TuningCode1
Compositional Learning of Visually-Grounded Concepts Using ReinforcementCode0
SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth EstimationCode1
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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