5 papers · 1 filter
DV-Lens: Revealing the Functional Organization of Language Model Parameters
Chenhang Cui, Jian Yu, Shuyi Miao +5
Understanding parameter functions helps elucidate the internal mechanisms of large language models (LLMs). However, how to connect parameters from different modules to verifiable o…
What Does Privileged Information Add to On-Policy Self-Distillation?
XiuYu Zhang, Wei Chow, Junfeng Fang +3
On-policy self-distillation (OPSD) lets a language model learn from a frozen copy of itself that sees an answer or a worked solution. Giving the teacher this extra information seem…
Preference-Aware Rubric Learning for Personalized Evaluation
Yilun Qiu, Xiaoyan Zhao, Yang Zhang +7
As Large Language Models (LLMs) evolve from general-purpose assistants to user-centric agents, personalization has become central to aligning model behavior with individual prefere…
Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversation
Jiani Luo, Xiaoyan Zhao, Yang Zhang +4
Personalized dialogue requires more than recalling explicit user histories: systems also need to infer hidden user states that evolve through interaction and shape appropriate resp…
MLLM-CTBench: A Benchmark for Continual Instruction Tuning with Reasoning Process Diagnosis
Haiyun Guo, Zhiyan Hou, Yandu Sun +6
Continual instruction tuning(CIT) during the post-training phase is crucial for adapting multimodal large language models (MLLMs) to evolving real-world demands. However, the progr…