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cs.CL2026

From Representations to Behaviors: Exploring the Person-Situation-Behavior Triad in LLMs

Ruikang Zhang, Shuo Wang, Qi Su

The paper investigates whether large language models (LLMs) have internal, trait-like personality representations that can be identified, manipulated, and shown to affect behavior…

cs.CL2026

FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding

Yingli Shen, Wen Lai, Jie Zhou +7

Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages. Existing resources impose a tr…

cs.CL2026

Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation

Rui Qi, Fengran Mo, Yufeng Chen +7

Multilingual retrieval-augmented generation (MRAG) requires models to effectively acquire and integrate beneficial external knowledge from multilingual collections. However, most e…

cs.CL2026

Mechanistic Knobs in LLMs: Retrieving and Steering High-Order Semantic Features via Sparse Autoencoders

Ruikang Zhang, Shuo Wang, Qi Su

Recent work in Mechanistic Interpretability (MI) has enabled the identification and intervention of internal features in Large Language Models (LLMs). However, a persistent challen…

cs.CL2026

Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction

Shuoxin Wang, Chang Liu, Gowen Loo +5

Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking perso…

cs.CL2025

LongCat-Flash Technical Report

Meituan LongCat Team, Bayan, Bei Li +179

We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…