314 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Hallucination models and implementations

Most implemented papers

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

adamian98/pulse CVPR 2020

We present an algorithm addressing this problem, PULSE (Photo Upsampling via Latent Space Exploration), which generates high-resolution, realistic images at resolutions previously unseen in the literature.

ReAct: Synergizing Reasoning and Acting in Language Models

ysymyth/ReAct 6 Oct 2022

While large language models (LLMs) have demonstrated impressive capabilities across tasks in language understanding and interactive decision making, their abilities for reasoning (e. g. chain-of-thought prompting) and acting (e. g. action plan generation) have primarily been studied as separate topics.

HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models

tianyi-lab/hallusionbench 23 Oct 2023

Our comprehensive case studies within HallusionBench shed light on the challenges of hallucination and illusion in LVLMs.

Im2Flow: Motion Hallucination from Static Images for Action Recognition

rhgao/Im2Flow CVPR 2018

Second, we show the power of hallucinated flow for recognition, successfully transferring the learned motion into a standard two-stream network for activity recognition.

Pushing the Limits of Low-Resource Morphological Inflection

antonisa/inflection IJCNLP 2019

Recent years have seen exceptional strides in the task of automatic morphological inflection generation.

On hallucinations in tomographic image reconstruction

uiuc-comp-imaging-sci/hallucinations-tomo-recon 1 Dec 2020

The behavior of different reconstruction methods under the proposed formalism is discussed with the help of the numerical studies.

Dataset Distillation via Factorization

huage001/datasetfactorization 30 Oct 2022

In this paper, we study \xw{dataset distillation (DD)}, from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.

Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

FuxiaoLiu/LRV-Instruction 26 Jun 2023

To efficiently measure the hallucination generated by LMMs, we propose GPT4-Assisted Visual Instruction Evaluation (GAVIE), a stable approach to evaluate visual instruction tuning like human experts.

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph

idea-finai/tog 15 Jul 2023

Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep and responsible reasoning.

Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer Learning

JalaliLabUCLA/Jalali-Lab-Implementation-of-RAISR 31 Jul 2018

A hallucination-free and computationally efficient algorithm for enhancing the resolution of brain MRI images is demonstrated.