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cs.CL2025

MMGR: Multi-Modal Generative Reasoning Benchmark and Evaluation

Zefan Cai, Haoyi Qiu, Tianyi Ma +13

Modern multimodal generative models can synthesize visually compelling images and videos, but it remains unclear whether this visual fluency reflects genuine reasoning: when prompt…

cs.CL2025

FaithLens: Detecting and Explaining Faithfulness Hallucination

Shuzheng Si, Qingyi Wang, Haozhe Zhao +8

Recognizing whether outputs from large language models (LLMs) contain faithfulness hallucination is crucial for real-world applications, e.g., retrieval-augmented generation and su…

cs.CL2025

A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks

Shuzheng Si, Haozhe Zhao, Kangyang Luo +5

Agents based on large language models (LLMs) struggle with brainless trial-and-error and generating hallucinatory actions due to a lack of global planning in long-horizon tasks. In…

cs.CL2025

Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning

Shuzheng Si, Haozhe Zhao, Cheng Gao +11

Teaching large language models (LLMs) to be faithful in the provided context is crucial for building reliable information-seeking systems. Therefore, we propose a systematic framew…

cs.CL2024

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey

Liang Chen, Zekun Wang, Shuhuai Ren +24

Building on the foundations of language modeling in natural language processing, Next Token Prediction (NTP) has evolved into a versatile training objective for machine learning ta…