Papers with Code 아카이브

Hallucination

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/imayk/crush4sql

공식 코드

CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQL

https://github.com/injadlu/damo

공식 코드

DAMO: Data- and Model-aware Alignment of Multi-modal LLMs

https://github.com/innodatalabs/innodata-llm-safety

공식 코드

Benchmarking Llama2, Mistral, Gemma and GPT for Factuality, Toxicity, Bias and Propensity for Hallucinations

https://github.com/internlm/agent-flan

공식 코드

Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models

https://github.com/intuit-ai-research/dcr-consistency

공식 코드

DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models

https://github.com/intuit/sac3

공식 코드

SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency

https://github.com/irlabamsterdam/cone-rag

공식 코드

Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets

https://github.com/itaymanes/k-qa

공식 코드

K-QA: A Real-World Medical Q&A Benchmark

https://github.com/ivrl/ccid

공식 코드

Image Denoising with Control over Deep Network Hallucination

https://github.com/ivy-lvlm/counterfactual-inception

공식 코드

What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models

https://github.com/j-bagel/treecut-math

공식 코드

TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination Evaluation

https://github.com/jadeleiyu/lm_hallucination_mechanisms

공식 코드

Mechanistic Understanding and Mitigation of Language Model Non-Factual Hallucinations

https://github.com/james-flemings/context_influence

공식 코드

Characterizing Context Influence and Hallucination in Summarization

https://github.com/janekh24/anhalten

공식 코드

ANHALTEN: Cross-Lingual Transfer for German Token-Level Reference-Free Hallucination Detection

https://github.com/javyduck/knowhalu

공식 코드

KnowHalu: Hallucination Detection via Multi-Form Knowledge Based Factual Checking

https://github.com/jaycening/dgot

공식 코드

DGoT: Dynamic Graph of Thoughts for Scientific Abstract Generation

https://github.com/jcruan519/vlrmbench

공식 코드

VLRMBench: A Comprehensive and Challenging Benchmark for Vision-Language Reward Models

https://github.com/jennycs0830/confidence_score_dst

공식 코드

Confidence Estimation for LLM-Based Dialogue State Tracking

https://github.com/jiahechen2002/dlc

공식 코드

Mitigating Hallucination of Large Vision-Language Models via Dynamic Logits Calibration

https://github.com/jianfeixu95/NCL-UoR

공식 코드

NCL-UoR at SemEval-2025 Task 3: Detecting Multilingual Hallucination and Related Observable Overgeneration Text Spans with Modified RefChecker and Modified SeflCheckGPT

https://github.com/jiangmeng-jm/cognitive-pathways---deep-learning

공식 코드

AI-Enhanced Cognitive Behavioral Therapy: Deep Learning and Large Language Models for Extracting Cognitive Pathways from Social Media Texts

https://github.com/jianguanthu/llmforfv

공식 코드

Language Models Hallucinate, but May Excel at Fact Verification

https://github.com/jiaqi5598/adavib

공식 코드

Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow

https://github.com/jiazhen-code/PhD

공식 코드

PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset

https://github.com/jihoonlee9898/rvcd

공식 코드

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models

https://github.com/jinhaoduan/truthprint

공식 코드

TruthPrInt: Mitigating LVLM Object Hallucination Via Latent Truthful-Guided Pre-Intervention

https://github.com/jinyeying/night-enhancement

공식 코드

Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression

https://github.com/jiuhaichen/florence-vl

공식 코드

Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion

https://github.com/joshua-ren/learning_dynamics_llm

공식 코드

Learning Dynamics of LLM Finetuning

https://github.com/journeybench/journeybench

공식 코드

JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images

https://github.com/junjun-jiang/Face-Hallucination-Benchmark

공식 코드

Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning

https://github.com/junjun-jiang/TLcR-RL

공식 코드

Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning

https://github.com/junyangwang0410/amber

공식 코드

AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

https://github.com/junyangwang0410/haelm

공식 코드

Evaluation and Analysis of Hallucination in Large Vision-Language Models

https://github.com/jusperlee/audiotrust

공식 코드

AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models

https://github.com/juyeonnn/reex

공식 코드

Re-Ex: Revising after Explanation Reduces the Factual Errors in LLM Responses

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.