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cs.CL2026
Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning
Zirui Song, Huaxing Liu, Xiang Wang +8
Prior white-box studies show that large language models can retain latent traces of target knowledge after unlearning, even when the knowledge is no longer expressed in their outpu…
cs.CL2026
CAVE: Competence-Aware Visual Boundary Evidence Alignment for Video Temporal Grounding
Wei Jia, Zhicong Lu, Yu Chen +5
Large vision-language models (LVLMs) have achieved substantial performance gains in Video Temporal Grounding (VTG) through reinforcement learning (RL). However, existing methods pr…
cs.CL2026
Faithful-MR1: Faithful Multimodal Reasoning via Anchoring and Reinforcing Visual Attention
Changyuan Tian, Zhicong Lu, Huaxing Liu +7
Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising paradigm for advancing complex reasoning in large language models, and recent work extends RLVR to…