activity
20202026
most citedContinual Learning for Large Language Models: A Survey

23 citations · 38 across the 31 of their papers we have counts for

collaborators
Showing 2026Show all

7 papers · 1 filter

cs.CL2026

UniGuard: Multi-View Guardrail Learning for Cross-Interface Safety Generalization

Viet-Thanh Pham, Thuy-Trang Vu, Junae Kim +4

Guardrail models are increasingly used as safety layers for LLMs and agentic systems, but most are trained on fixed prompt or response interfaces and become unreliable when the sam…

cs.AI2026

Anticipating Social Consequences with Distributional World Models

Viet-Thanh Pham, Thuy-Trang Vu, Zhuang Li +2

Social world models predict how interactions develop after an action, helping agents negotiate, cooperate and mediate. In these situations, one action can lead to several plausible…

cs.MA2026

A Responsibility-Centered Coordination Mechanism for Decentralized Multi-Agent Systems

Thi-Nhung Nguyen, Viet-Thanh Pham, Linhao Luo +2

Centralized orchestration provides comprehensive multi-agent coordination but creates bottlenecks in scalability, adaptability, and collective performance. Decentralized approaches…

cs.CL2026

E-Orch: Towards Effective, Efficient, and Extensible Agentic Orchestration with Reinforcement Learning

Junnan Liu, Linhao Luo, Thuy-Trang Vu +1

Agentic orchestration enables multiple autonomous agents to solve complex tasks through adaptive decomposition, delegation, and execution. However, existing orchestrators often rel…

cs.CL2026

AIPO: Learning to Reason from Active Interaction

Junnan Liu, Linhao Luo, Thuy-Trang Vu +1

Recent advances in LLMs have demonstrated strong reasoning capabilities, largely stimulated by RLVR. However, the exploration of existing RLVR algorithms remains largely constraine…

cs.CL2026

GTS: Inference-Time Scaling of Latent Reasoning with a Learnable Gaussian Thought Sampler

Minghan Wang, Ye Bai, Thuy-Trang Vu +2

Inference-time scaling (ITS) in latent reasoning models typically relies on heuristic perturbations, such as dropout or fixed Gaussian noise, to generate diverse candidate trajecto…

cs.AI2026

LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations

Viet-Thanh Pham, Lizhen Qu, Thuy-Trang Vu +2

Large language models (LLMs) are increasingly deployed as autonomous agents, yet evaluations focus primarily on task success rather than cultural appropriateness or evaluator relia…