:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lee, Namkyeong, Laghuvarapu, Siddhartha, Park, Chanyoung, Sun, Jimeng
Format:	Preprint
Publié:	2024
Sujets:	Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2407.09043
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

KMM-CP: Practical Conformal Prediction under Covariate Shift via Selective Kernel Mean Matching
par: Laghuvarapu, Siddhartha, et autres
Publié: (2026)

ConfHit: Conformal Generative Design with Oracle Free Guarantees
par: Laghuvarapu, Siddhartha, et autres
Publié: (2026)

MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
par: Noh, Heewoong, et autres
Publié: (2026)

Molecular De Novo Design through Transformer-based Reinforcement Learning
par: Xu, Pengcheng, et autres
Publié: (2023)

Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge
par: Noh, Heewoong, et autres
Publié: (2024)

Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification
par: Chatterjee, Arjun, et autres
Publié: (2026)

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra
par: Noh, Heewoong, et autres
Publié: (2025)

Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions
par: Lee, Jeongeun, et autres
Publié: (2026)

Text is All You Need for Vision-Language Model Jailbreaking
par: Chen, Yihang, et autres
Publié: (2026)

RAG-Enhanced Collaborative LLM Agents for Drug Discovery
par: Lee, Namkyeong, et autres
Publié: (2025)

Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models
par: Yu, Lu, et autres
Publié: (2024)

Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System
par: Kim, Sein, et autres
Publié: (2024)

All You Need Is Synthetic Task Augmentation
par: Godin, Guillaume
Publié: (2025)

3D Interaction Geometric Pre-training for Molecular Relational Learning
par: Lee, Namkyeong, et autres
Publié: (2024)

Subgraph Federated Learning for Local Generalization
par: Kim, Sungwon, et autres
Publié: (2025)

Guidance is All You Need: Temperature-Guided Reasoning in Large Language Models
par: Gomaa, Eyad, et autres
Publié: (2024)

Consensus Is All You Need: Gossip-Based Reasoning Among Large Language Models
par: Arora, Saksham
Publié: (2025)

LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
par: Huang, Linghan, et autres
Publié: (2025)

Belief Is All You Need: Modeling Narrative Archetypes in Conspiratorial Discourse
par: Shimgekar, Soorya Ram, et autres
Publié: (2025)

Vision Language Models See What You Want but not What You See
par: Gao, Qingying, et autres
Publié: (2024)

Beyond Label Attention: Transparency in Language Models for Automated Medical Coding via Dictionary Learning
par: Wu, John, et autres
Publié: (2024)

Modeling Code: Is Text All You Need?
par: Nichols, Daniel, et autres
Publié: (2025)

PAIR: Prefix-Aware Internal Reward Model for Multi-Turn Agent Optimization
par: Kim, Wonjoong, et autres
Publié: (2026)

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
par: Wen, Yilin, et autres
Publié: (2023)

Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis
par: Lee, Haeil, et autres
Publié: (2024)

Cognition is All You Need -- The Next Layer of AI Above Large Language Models
par: Spivack, Nova, et autres
Publié: (2024)

Reasoning Structure Matters for Safety Alignment of Reasoning Models
par: In, Yeonjun, et autres
Publié: (2026)

FineVision: Open Data Is All You Need
par: Wiedmann, Luis, et autres
Publié: (2025)

AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Models
par: Cao, Lang, et autres
Publié: (2024)

Are Retrials All You Need? Enhancing Large Language Model Reasoning Without Verbalized Feedback
par: Potamitis, Nearchos, et autres
Publié: (2025)

Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
par: Kim, Wonjoong, et autres
Publié: (2025)

Attention is All You Need Until You Need Retention
par: Yaslioglu, M. Murat
Publié: (2025)

Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks
par: Kim, Sungwon, et autres
Publié: (2025)

Randomness Is All You Need: Semantic Traversal of Problem-Solution Spaces with Large Language Models
par: Sandholm, Thomas, et autres
Publié: (2024)

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization
par: Fu, Tianfan, et autres
Publié: (2020)

s3: You Don't Need That Much Data to Train a Search Agent via RL
par: Jiang, Pengcheng, et autres
Publié: (2025)

Common Sense Is All You Need
par: Latapie, Hugo
Publié: (2025)

Contrast Is All You Need
par: Kilic, Burak, et autres
Publié: (2023)

Context is All You Need
par: Delanois, Jean Erik, et autres
Publié: (2026)

R1-ACT: Efficient Reasoning Model Safety Alignment by Activating Safety Knowledge
par: In, Yeonjun, et autres
Publié: (2025)