activity
20232026
most citedLLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition

12 citations · 80 across the 115 of their papers we have counts for

collaborators

143 papers

cs.CL2026

Agents in the Large: Perception-Centered Architecture for Persistent Agents

Shihan Dou, Haoxiang Jia, Shichun Liu +14

Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling agents to reason and act in i…

cs.LG2026

A Token-Level Analysis of Sampled-Token Reverse-KL On-Policy Distillation

Bing Shao, Jiazheng Zhang, Long Ma +11

On-policy distillation (OPD) supervises a student on its own trajectories with token-level signals from a frozen teacher, yet how a sampled loss allocates updates across tokens rem…

cs.AI2026

CAFE: Self-Improving Search Agents Need Co-Evolving Feedback

Boyang Liu, Senjie Jin, Peixin Wang +17

Reliable search requires more than acquiring external evidence. An agent must also recognize and recover from errors as its trajectory unfolds. In-trajectory feedback provides a me…

cs.SD2026

MuseCritic: Learning Multi-Aspect Song Rewards through Natural-Language Aesthetic Critiques

Jiabao Zhuang, Changhao Jiang, Hanchen Wang +11

Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards increasingly important for aligni…

cs.CL2026

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

Junjie Ye, Zhuohui Sheng, Shaofan Liu +12

Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps)…

cs.CL2026

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

Dingwei Zhu, Jiahan Li, Chengjun Pan +22

Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustness via implicit history sca…