Author

Tieniu Tan

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Preprint Jul 2026

AgentStream: How Well Do Self-Evolving LLM Agents Perform Under Streaming Tasks?

Large language model (LLM) agents can self-evolve by continually improving from their own accumulated experience. However, existing studies predominantly adopt independent evaluation. Consequently, the behavior of self-evolving agents in realistic streaming settings, where agents adapt to diverse and complex task strea...

Dong Yan, Jian Liang, Dapeng Hu et al. · 0 citations

#machine learning Preprint Sep 2026

To Adapt or Not to Adapt? Selective Adaptation for Vision-Language Models

Test-time adaptation (TTA) has emerged as a prominent strategy for adapting vision-language models to distribution shifts during inference. We conduct a per-sample analysis of model predictions before and after adaptation, and observe two failure modes in existing TTA methods that echo previous work. Adaptations are fr...

Si-Ru Jiang, Yu-Wei Liang, Jian Liang et al. · 1 citation

Preprint Jul 2026

USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning

Test-time adaptation (TTA) has emerged as a popular paradigm for improving the performance of vision-language models (e.g., CLIP) on downstream tasks. Among existing CLIP-based TTA methods, Test-Time Prompt Tuning (TPT) is a pioneering work that optimizes textual prompts using multiple test-time augmentations and remai...

Siru Jiang, Jian Liang, Ran He et al. · 0 citations