works on

From the 1 of 29 linked papers with an AI index.

activity
20242026
most citedTowards Interpretable Federated Learning

10 citations · 13 across the 10 of their papers we have counts for

collaborators

29 papers

cs.CL2026

Reinforcing Step-level Reasoning for Effective Self-Correction in LLMs

Vu Duc Anh, Nhat M. Hoang, Do Xuan Long +3

Achieving effective self-correction, where models verify and correct their own mistakes, remains a fundamental challenge for large language models (LLMs). In this work, we propose…

cs.CL2026

TIGER: Text-Conditioned Visual Gated Routing with Acceptance Alignment for Multimodal Speculative Decoding

Quynh Vo, Cong-Duy Nguyen, Ponhvoan Srey +2

The paper introduces TIGER, a framework that speeds up multimodal generation by dynamically selecting only the visual tokens relevant to the current textual context and training th…

cs.AI2026

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

Mingzhe Du, Luu Anh Tuan, Tianyi Wu +4

Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar that reaches a vulnerable path,…

cs.AI20261 cited

A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications

Wenyi Xiao, Zechuan Wang, Leilei Gan +9

With the rapid advancement of large language models (LLMs), aligning policy models with human preferences has become increasingly critical. Direct Preference Optimization (DPO) has…

cs.CL20261 cited

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Haoran Luo, Haihong E, Guanting Chen +8

Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that lacks structural semantics. Graph…

cs.LG202610 cited

Towards Interpretable Federated Learning

Anran Li, Rui Liu, Ming Hu +4

Federated learning (FL) enables multiple data owners to build machine learning models collaboratively without exposing their private local data. In order for FL to achieve widespre…