works on

From the 2 of 15 linked papers with an AI index.

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

1 citations · 1 across the 4 of their papers we have counts for

collaborators

15 papers

cs.CL2026

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…

cs.CL2026

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…

cs.AI2026

Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents

Shiyu Ying, Xuejie Cao, Yingfan Ma +4

The paper introduces Alipay-PIBench, a benchmark that evaluates coding agents on realistic Alipay payment integration tasks, covering functional completion and risk-aware hardening…

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.LG2026

OPRD: On-Policy Representation Distillation

Shenzhi Yang, Guangcheng Zhu, Bowen Song +8

On-policy distillation (OPD) supervises the student exclusively in the output space by matching next-token distributions. This paradigm suffers from two limitations: (i) a high-var…