From the 1 of 13 linked papers with an AI index.
1 citations · 1 across the 8 of their papers we have counts for
6 papers · 1 filter
EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents
Jianan Xie, Xin Sun, Zhongqi Chen +4
Outcome-based reinforcement learning enables search-augmented language agents to learn from verifiable final answers, but its trajectory-level credit cannot distinguish the contrib…
HopRefusalBench: Diagnosing Refusal Failures in Search-Augmented Agents for Multi-Hop Reasoning
Jianan Xie, Xin Sun, Zhongqi Chen +3
Search-augmented large language model agents are increasingly capable of solving knowledge-intensive tasks, but their behavior when a multi-hop question is fundamentally unanswerab…
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…
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…
GAPD: Gold-Action Policy Distillation for Agentic Reinforcement Learning in Knowledge Base Question Answering
Xin Sun, Jianan Xie, Zhongqi Chen +6
Reinforcement learning (RL) is a natural fit for agentic knowledge base question answering (KBQA), where a model must issue executable actions, observe knowledge-base feedback, and…
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…