HINT

Hierarchical Information Threading

Introduced 2000115 papers

Description

An unsupervised approach for identifying Hierarchical Information Threads by analysing the network of related articles in a collection. In particular, HINT leverages article timestamps and the 5W1H questions to identify related articles about an event or discussion. HINT then constructs a network representation of the articles, and identify threads as strongly connected hierarchical network communities.

Papers Using This Method

The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements2025-06-27Generative Blocks World: Moving Things Around in Pictures2025-06-25On the efficacy of old features for the detection of new bots2025-06-24HI-SQL: Optimizing Text-to-SQL Systems through Dynamic Hint Integration2025-06-11LeanTutor: A Formally-Verified AI Tutor for Mathematical Proofs2025-06-10Training-Free Query Optimization via LLM-Based Plan Similarity2025-06-06MIRAGE: Assessing Hallucination in Multimodal Reasoning Chains of MLLM2025-05-30Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks2025-05-19The Promise and Limits of LLMs in Constructing Proofs and Hints for Logic Problems in Intelligent Tutoring Systems2025-05-07Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning2025-05-06"I Know It When I See It": Mood Spaces for Connecting and Expressing Visual Concepts2025-04-21ColorVein: Colorful Cancelable Vein Biometrics2025-04-19LayerFlow: Layer-wise Exploration of LLM Embeddings using Uncertainty-aware Interlinked Projections2025-04-09MKA: Leveraging Cross-Lingual Consensus for Model Abstention2025-03-31Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image Restoration2025-03-26ML-Triton, A Multi-Level Compilation and Language Extension to Triton GPU Programming2025-03-19Inside-Out: Hidden Factual Knowledge in LLMs2025-03-19High-Dimensional Interlingual Representations of Large Language Models2025-03-14The Space Between: On Folding, Symmetries and Sampling2025-03-11START: Self-taught Reasoner with Tools2025-03-06