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cs.CL2026

Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction

Shuoxin Wang, Chang Liu, Gowen Loo +5

Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking perso…

cs.CL2026

ES-Mem: Event Segmentation-Based Memory for Long-Term Dialogue Agents

Huhai Zou, Tianhao Sun, Chuanjiang He +6

Memory is critical for dialogue agents to maintain coherence and enable continuous adaptation in long-term interactions. While existing memory mechanisms offer basic storage and re…

cs.CL2026

DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models

Shaokai He, Kaiwen Wei, Xinyi Zeng +5

The "reversal curse" refers to the phenomenon where large language models (LLMs) exhibit predominantly unidirectional behavior when processing logically bidirectional relationships…

cs.CL2026

ReasonTabQA: A Comprehensive Benchmark for Table Question Answering from Real World Industrial Scenarios

Changzai Pan, Jie Zhang, Kaiwen Wei +15

Recent advancements in Large Language Models (LLMs) have significantly catalyzed table-based question answering (TableQA). However, existing TableQA benchmarks often overlook the i…

cs.CL2025

CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation

Kaiwen Wei, Xiao Liu, Jie Zhang +11

Multimodal Retrieval-Augmented Generation (MRAG) enables Multimodal Large Language Models (MLLMs) to generate responses with external multimodal evidence, and numerous video-based…

cs.CL2025

T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tables

Jie Zhang, Changzai Pan, Kaiwen Wei +12

Extensive research has been conducted to explore the capabilities of large language models (LLMs) in table reasoning. However, the essential task of transforming tables information…