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AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents
Xiangchen Cheng, Yunwei Jiang, Jianwen Sun +7
Memory for a long-horizon LLM agent is a contract about what each future decision is allowed to see. The simplest contract appends past observations, tool calls, and reflections to…
Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection
Fanrui Zhang, Qiang Zhang, Sizhuo Zhou +10
Existing image forgery detection (IFD) methods either exploit low-level, semantics-agnostic artifacts or rely on multimodal large language models (MLLMs) with high-level semantic k…
Closing the Expression Gap in LLM Instructions via Socratic Questioning
Jianwen Sun, Yukang Feng, Yifan Chang +6
A fundamental bottleneck in human-AI collaboration is the ``intention expression gap," the difficulty for humans to effectively convey complex, high-dimensional thoughts to AI. Thi…
InMind: Evaluating LLMs in Capturing and Applying Individual Human Reasoning Styles
Zizhen Li, Chuanhao Li, Yibin Wang +8
LLMs have shown strong performance on human-centric reasoning tasks. While previous evaluations have explored whether LLMs can infer intentions or detect deception, they often over…
MDK12-Bench: A Comprehensive Evaluation of Multimodal Large Language Models on Multidisciplinary Exams
Pengfei Zhou, Xiaopeng Peng, Fanrui Zhang +18
Multimodal large language models (MLLMs), which integrate language and visual cues for problem-solving, are crucial for advancing artificial general intelligence (AGI). However, cu…
ProJudge: A Multi-Modal Multi-Discipline Benchmark and Instruction-Tuning Dataset for MLLM-based Process Judges
Jiaxin Ai, Pengfei Zhou, Zhaopan Xu +8
As multi-modal large language models (MLLMs) frequently exhibit errors when solving scientific problems, evaluating the validity of their reasoning processes is critical for ensuri…