7 papers
SWEeper-Bench: Can Agents Discover Bugs in Interactive Software?
Yang Yao, Haozhe Chen, Bingyi Kang +2
Coding agents increasingly interact with users by generating interactive software on the fly rather than replying in text, yet many bugs in such software reveal themselves only aft…
Caught in the Story: Narrative Captivity in Multi-turn LLMs Conversation
Yuhe Wu, Guangyu Wang, Yujie Chen +7
People increasingly turn to large language models (LLMs) for everyday advice, making ethically charged interpersonal problems a practical moral-advisory context. Most prior work ha…
CEO-Bench: Can Agents Play the Long Game?
Haozhe Chen, Karthik Narasimhan, Zhuang Liu
Language model agents are becoming proficient executors at isolated, short-horizon tasks such as software engineering and customer service. Yet real-world challenges require a comb…
End-to-End Context Compression at Scale
Ang Li, Sean McLeish, Haozhe Chen +12
Long-context language model inference is bottlenecked by memory, as the KV cache grows with context length. Recent techniques to compress the KV cache fall short: they either degra…
PRISM: Probing Reasoning, Instruction, and Source Memory in LLM Hallucinations
Yuhe Wu, Guangyu Wang, Yuran Chen +6
As large language models (LLMs) evolve from conversational assistants into agents capable of handling complex tasks, they are increasingly deployed in high-risk domains. However, e…
HyperGVL: Benchmarking and Improving Large Vision-Language Models in Hypergraph Understanding and Reasoning
Yanbin Wei, Chun Kang, Siwei Li +11
Large Vision-Language Models (LVLMs) consistently require new arenas to guide their expanding boundaries, yet their capabilities with hypergraphs remain unexplored. In the real wor…
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark
Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan +6
Rapid advancements in large language models (LLMs) have increased interest in deploying them on mobile devices for on-device AI applications. Mobile users interact differently with…