SOTAVerified

Open-Ended Question Answering

Open-ended questions are defined as those that simply pose the question, without imposing any constraints on the format of the response. This distinguishes them from questions with a predetermined answer format.

Papers

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Showing 151–175 of 796 papers

TitleStatusHype
A Quantitative Review on Language Model Efficiency Research—0
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise—0
Aligning Language Models to User Opinions—0
SAIL: Search-Augmented Instruction Learning—0
Routing by spontaneous synchronization—0
Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsCode0
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLPCode0
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs—0
Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension—0
Spiking Network Initialisation and Firing Rate Collapse—0
Reduced Label Complexity For Tight _2 Regression—0
A Generic Approach to Integrating Time into Spatial-Temporal Forecasting via Conditional Neural Fields—0
The Role of Relevance in Fair RankingCode0
Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space—0
Development of a Trust-Aware User Simulator for Statistical Proactive Dialog Modeling in Human-AI Teams—0
Evolving Three Dimension (3D) Abstract Art: Fitting Concepts by Language—0
How the Move Acceptance Hyper-Heuristic Copes With Local Optima: Drastic Differences Between Jumps and Cliffs—0
Image retrieval outperforms diffusion models on data augmentation—0
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets—0
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study—0
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural NetworksCode0
Lipschitz Continuity of Signal Temporal Logic Robustness Measures: Synthesizing Control Barrier Functions from One Expert Demonstration—0
Krylov Methods are (nearly) Optimal for Low-Rank Approximation—0
AutoRL Hyperparameter LandscapesCode0
Feature representations useful for predicting image memorability—0
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