#training-free methods
16 papers · 1 filter
ViewMind3D: Modular View-Aware Inference for Training-Free 3D-QA
Ping-Kun Chiang, Kun-Ru Wu, Po-han Li +3
ViewMind3D is a training‑free, modular framework that answers 3D questions by selecting relevant views, grounding objects with language cues, encoding spatial context via a bird's‑…
Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models
Jie Ma, Zhike Qiu, Jie Gao +4
The paper introduces Trend-aware Pruning, a training‑free method that models the temporal dynamics of attention to selectively keep visual tokens that become important in deeper la…
LAST: The Last Query Token Guides Visual Token Pruning for Edge-Cloud Collaborative MLLM Inference
Feng Yang, Xinrui Ju, Keyang Zhang +6
The paper introduces LAST, a training‑free method that uses the attention of the last query token to prune visual tokens on edge devices before sending them to a cloud multimodal L…
Prox: Training-Free FFN Activation Sparsity via Approximate Intermediate-Channel Salience in LLMs
Jinyi Liu, Wei Chen, Pengyu Chen +4
The paper introduces Prox, a training-free framework that sparsifies feed‑forward network activations in large language models by approximating intermediate‑channel salience, enabl…
FreqForcing: Autoregressive Long Video Generation via Spectral Self-Anchoring
Jiatong Li, Leo Liang, Linghe Kong +1
The paper introduces FreqForcing, a training‑free method that uses spectral self‑anchoring to counter low‑frequency energy drift and improve visual stability in autoregressive long…
TraceCLIP: Recovering Local Semantics from Patch-to-CLS Contributions
Xinran Liu, Shouqian Shi, Yutong Chen +3
The paper presents TraceCLIP, a training‑free method that extracts patch‑level semantic information from CLIP's CLS attention output to improve zero‑shot dense vision‑language task…