Search Results for author:
Found 8 papers, 4 papers with code
MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness
With the widespread application of large language models (LLMs), the issue of generating non-existing facts, known as hallucination, has garnered increasing attention.
Enhancing Language Multi-Agent Learning with Multi-Agent Credit Re-Assignment for Interactive Environment Generalization
To address these issues, we propose CollabUIAgents, a multi-agent reinforcement learning framework with a novel multi-agent credit re-assignment (CR) strategy, assigning process rewards with LLMs rather than environment-specific rewards and learning with synthesized preference data, in order to foster generalizable, collaborative behaviors among the role-free agents' policies.
Group-Adaptive Threshold Optimization for Robust AI-Generated Text Detection
The advancement of large language models (LLMs) has made it difficult to differentiate human-written text from AI-generated text.
CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering
To address this, we explore the Cross-Lingual Self-Aligning ability of Language Models (CALM) to align knowledge across languages.
Schema-Guided Culture-Aware Complex Event Simulation with Multi-Agent Role-Play
Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society.
MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders
In this paper, we introduce MentalArena, a self-play framework to train language models by generating domain-specific personalized data, where we obtain a better model capable of making a personalized diagnosis and treatment (as a therapist) and providing information (as a patient).
Aligning LLMs with Individual Preferences via Interaction
To address this gap, we train LLMs that can ''interact to align'', essentially cultivating the meta-skill of LLMs to implicitly infer the unspoken personalized preferences of the current user through multi-turn conversations, and then dynamically align their following behaviors and responses to these inferred preferences.
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Propaganda plays a critical role in shaping public opinion and fueling disinformation.
