新闻
Predicting the Performance of Black-box LLMs through Self-Queries
arXiv:2501.01558v3 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly relied on in...
Precise Attribute Intensity Control in Large Language Models via Targeted Representation Editing
arXiv:2510.12121v1 Announce Type: cross Abstract: Precise attribute intensity control–generating Large Language Model (LLM) outputs with...
Pre-trained Transformer-Based Approach for Arabic Question Answering : A Comparative Study
arXiv:2111.05671v2 Announce Type: replace Abstract: Question answering(QA) is one of the most challenging yet widely...
Pragmatic Reasoning improves LLM Code Generation
arXiv:2502.15835v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive potential in translating...
Post-LayerNorm Is Back: Stable, ExpressivE, and Deep
arXiv:2601.19895v1 Announce Type: cross Abstract: Large language model (LLM) scaling is hitting a wall. Widening...
Position: The Real Barrier to LLM Agent Usability is Agentic ROI
arXiv:2505.17767v2 Announce Type: replace Abstract: Large Language Model (LLM) agents represent a promising shift in...
Pose-Based Sign Language Appearance Transfer
arXiv:2410.13675v2 Announce Type: replace-cross Abstract: We introduce a method for transferring the signer’s appearance in...
PolyAI Releases Dialog-RSN-1: An Audio-Native Dialog Model That Fuses Turn-Taking, Speech Recognition, Function Calling, And Response
PolyAI has introduced Dialog-RSN-1, a dialog model that perceives the caller’s audio directly instead of...
Political Leaning and Politicalness Classification of Texts
arXiv:2507.13913v1 Announce Type: new Abstract: This paper addresses the challenge of automatically classifying text according...
PoE-World + Planner Outperforms Reinforcement Learning RL Baselines in Montezuma’s Revenge with Minimal Demonstration Data
The Importance of Symbolic Reasoning in World Modeling Understanding how the world works is key...
PLAN-TUNING: Post-Training Language Models to Learn Step-by-Step Planning for Complex Problem Solving
arXiv:2507.07495v1 Announce Type: new Abstract: Recently, decomposing complex problems into simple subtasks–a crucial part of...
Pie day links
Pie Day at the Massachusetts Institute of Tasteology...
