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20232026
most citedCodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification

4 citations · 11 across the 30 of their papers we have counts for

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13 papers · 1 filter

cs.LG2026

LoOPSD: On-Policy Self-Distillation with Looped Teachers

Wei Fan, Qingyue Yang, Chao-Hong Tan +6

On-policy self-distillation improves a model using guidance from the model itself, but it still requires a teacher that provides more useful predictions than the student. Existing…

cs.CL2026

ConsensusBench: Benchmark of Consensus Nodes for LLM Reasoning via Outcome Reward Densifying

Shi-Qi Yan, Chao-Hong Tan, Qian Chen +3

Reinforcement learning (RL) has become one of the primary paradigms for reasoning enhancement of large language models (LLMs). In particular, Group Relative Policy Optimization (GR…

cs.CL2026

Short Horizons and Sparse Concepts: a Mathematical View of the Readout in the J-lens

Shi-Qi Yan, Kai-Xuan Ding, Chao-Hong Tan +4

The Jacobian lens (J-lens) has been proposed as a way to read verbalizable representations from language models. However, its principle and meaning lack a detailed and theoretical…

cs.CL2026

Efficient Chain-of-Modality Reasoning via Progressive Compression for Spoken Language Models

Pengchao Feng, Chao-Hong Tan, Qian Chen +3

Spoken language models (SLMs) enable natural human-computer interaction, but their reasoning ability still lags behind that of text-based large language models, especially on spoke…

eess.AS2026

AudioCALM: Continuous Autoregressive Language Modeling for Universal Audio Generation

Huadai Liu, Kaicheng Luo, Wen Wang +4

Unifying speech, sound, and music generation in one model is hindered by tradeoffs between fidelity, end-to-end training, in-context conditioning, and variable-length synthesis tha…

eess.AS2026

STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation

Huadai Liu, Wen Wang, Kaicheng Luo +3

Continuous Variational Autoencoders (VAEs) serve as the fundamental continuous tokenizer for modern neural audio generation systems, enabling high-fidelity reconstruction while pro…

eess.AS2026

BareWave: Waveform-Native Flow-Matching Text-to-Speech

Wei Fan, Chao-Hong Tan, Qian Chen +5

Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling. In text-to-speech, however, high-quality syst…

cs.SD2026

UniVocal: Unified Speech-Singing Code-Switching Synthesis

Yufei Shi, Qian Chen, Wen Wang +3

We propose UniVocal, a unified framework that implicitly infers vocal modes from text context to pioneer Speech-Singing Code-Switching (SCS) Synthesis - a task where transitions ar…

cs.RO2026

LEGS: Fine-Tuning Teleop-Free VLAs for Humanoid Loco-manipulation in an Embodied Gaussian Splatting World

Hojune Kim, Timothy Chen, Jiankai Sun +4

Training vision-language-action (VLA) policies for humanoid loco-manipulation is constrained by the high cost and complexity of collecting human teleoperation demonstrations. VLA p…

cs.AI2026

WavAlign: Enhancing Intelligence and Expressiveness in Spoken Dialogue Models via Adaptive Hybrid Post-Training

Yifu Chen, Shengpeng Ji, Qian Chen +9

End-to-end spoken dialogue models have garnered significant attention because they offer a higher potential ceiling in expressiveness and perceptual ability than cascaded systems.…

cs.AI2026

Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models

Yifu Chen, Shengpeng Ji, Zhengqing Liu +6

Achieving seamless, human-like interaction remains a key challenge for full-duplex spoken dialogue models (SDMs). Reinforcement learning (RL) has substantially enhanced text- and v…

cs.LG2026

FGGM: Fisher-Guided Gradient Masking for Continual Learning

Chao-Hong Tan, Qian Chen, Wen Wang +6

Catastrophic forgetting impairs the continuous learning of large language models. We propose Fisher-Guided Gradient Masking (FGGM), a framework that mitigates this by strategically…

cs.CL2026★ 1 cited

Fun-Audio-Chat Technical Report

Tongyi Fun Team, Qian Chen, Luyao Cheng +10

Recent advancements in joint speech-text models show great potential for seamless voice interactions. However, existing models face critical challenges: temporal resolution mismatc…