Can large language models explore in-context?
Paper
•
2403.15371
•
Published
•
31
LLM
-
-
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 43 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 34 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 59 -
CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues
Paper • 2404.03820 • Published • 23 -
Social Skill Training with Large Language Models
Paper • 2404.04204 • Published • 15 -
Stream of Search (SoS): Learning to Search in Language
Paper • 2404.03683 • Published • 21 -
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Paper • 2404.05961 • Published • 63 -
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 39 -
Predicting Rewards Alongside Tokens: Non-disruptive Parameter Insertion for Efficient Inference Intervention in Large Language Model
Paper • 2408.10764 • Published • 7 -
OLMoE: Open Mixture-of-Experts Language Models
Paper • 2409.02060 • Published • 74 -
Attention Heads of Large Language Models: A Survey
Paper • 2409.03752 • Published • 83 -
Building Math Agents with Multi-Turn Iterative Preference Learning
Paper • 2409.02392 • Published • 14 -
DSBench: How Far Are Data Science Agents to Becoming Data Science Experts?
Paper • 2409.07703 • Published • 56 -
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Paper • 2409.08264 • Published • 37 -
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Paper • 2409.04109 • Published • 35