6 papers · 1 filter
SEAR: Spoofing Evidence-Grounded Audio Reasoning Benchmark for Audio Language Models
Rong Wan, Suliu Qin, Jiaxi Li +5
Audio language models (ALMs) are increasingly used for audio deepfake detection (ADD), yet existing benchmarks assess their verdicts or rationale plausibility without verifying the…
SE-ADD: Self-Evolving Audio Deepfake Detection with Mistake-Driven Supervision
Rong Wan, Wei Xie, Jiaxi Li +4
Audio deepfake detection (ADD) must remain effective when new spoofing attacks emerge after deployment. Emerging audio language model (ALM)-based ADD methods are built on predefine…
Grounded Checklist Partial Credit for Agent Skill Trajectories
Suliu Qin, Lu Yin, Xilu Wang
Language-model agents increasingly tackle long-horizon tasks in interactive environments, yet their evaluation commonly relies on task-level success rates by reducing an entire exe…
ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity
Jiaxi Li, Lu Yin, Li Shen +5
Large Language Models (LLMs) have achieved remarkable capabilities, but their immense computational demands during training remain a critical bottleneck for widespread adoption. Lo…
Long Chain-of-Thought Compression via Fine-Grained Group Policy Optimization
Xinchen Han, Hossam Afifi, Michel Marot +2
Large Language Models (LLMs) often generate unnecessarily verbose Chain-of-Thought (CoT) reasoning that increases computational costs and latency without proportional performance g…
Search or Accelerate: Confidence-Switched Position Beam Search for Diffusion Language Models
Mingyu Cao, Alvaro H. C. Correia, Christos Louizos +2
Diffusion Language Models (DLMs) generate text by iteratively denoising a masked sequence, repeatedly deciding which positions to commit at each step. Standard decoding follows a g…