works on

From the 1 of 46 linked papers with an AI index.

activity
20242026
most citedPredict the Retrieval! Test time adaptation for Retrieval Augmented Generation

1 citations · 3 across the 9 of their papers we have counts for

collaborators
Showing cs.CLShow all

15 papers · 1 filter

cs.CL20261 cited

Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation

Xin Sun, Zhongqi Chen, Qiang Liu +5

The paper introduces TTARAG, a test-time adaptation technique that updates a language model's parameters during inference to better integrate retrieved knowledge for specialized do…

cs.CL2026

KBQA-R1: Reinforcing Large Language Models for Knowledge Base Question Answering

Xin Sun, Zhongqi Chen, Xing Zheng +6

Knowledge Base Question Answering (KBQA) challenges models to bridge the gap between natural language and strict knowledge graph schemas by generating executable logical forms. Whi…

cs.CL2026

NAG: A Unified Native Architecture for Encoder-free Text-Graph Modeling in Language Models

Haisong Gong, Zhibo Liu, Qiang Liu +2

Prevailing methods for integrating graphs into Language Models (LMs) typically rely on a segregated architecture: external Graph Neural Networks (GNNs) encode structural topology,…

cs.CL2025

Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models

Qiang Liu, Xinlong Chen, Yue Ding +4

Hallucination has emerged as a significant barrier to the effective application of Large Language Models (LLMs). In this work, we introduce a novel Attention-Guided SElf-Reflection…

cs.CL2025

Uncovering Overfitting in Large Language Model Editing

Mengqi Zhang, Xiaotian Ye, Qiang Liu +3

Knowledge editing has been proposed as an effective method for updating and correcting the internal knowledge of Large Language Models (LLMs). However, existing editing methods oft…

cs.CL2025

Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG

Xin Sun, Jianan Xie, Zhongqi Chen +7

Large language models (LLMs) augmented with retrieval systems have significantly advanced natural language processing tasks by integrating external knowledge sources, enabling more…