5 papers
StreamTTT: Reconciling Real-Time Perception and Long-Term Memory in Streaming VLMs
Joya Chen, Zeyun Zhong, Mike Zheng Shou
Humans effortlessly perceive the present while remembering the past, yet streaming VLMs often trade off real-time perception against long-term memory. Prior work shows that shorten…
BaseCal: Unsupervised Confidence Calibration via Base Model Signals
Hexiang Tan, Wanli Yang, Junwei Zhang +7
Reliable confidence is essential for trusting the outputs of LLMs, yet widely deployed post-trained LLMs (PoLLMs) typically compromise this trust with severe overconfidence. In con…
Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
Chenyu Lin, Yilin Wen, Du Su +5
Retrieval-augmented generation (RAG) improves performance on knowledge-intensive tasks but can be derailed by wrong, irrelevant, or conflicting retrieved text, causing models to re…
A Survey on LLM-as-a-Judge
Jiawei Gu, Xuhui Jiang, Zhichao Shi +13
Accurate and consistent evaluation is crucial for decision-making across numerous fields, yet it remains a challenging task due to inherent subjectivity, variability, and scale. La…
Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs
Hexiang Tan, Fei Sun, Sha Liu +8
As large language models (LLMs) often generate plausible but incorrect content, error detection has become increasingly critical to ensure truthfulness. However, existing detection…