arXiv:2605.01834v1 Announce Type: cross
Abstract: Contrastive learning (CL) reduces annotation cost via auto-derived supervisory signals. Since large-scale in-house CL datasets are infeasible, reliance on third-party or internet data is common. Recent…
arXiv:2604.09111v4 Announce Type: replace-cross
Abstract: Recently, artificial intelligence-based dubbing technology has advanced, enabling automated dubbing (AD) to convert the source speech of a video into target speech in different languages. Howev…
arXiv:2605.03372v1 Announce Type: new
Abstract: Future imaging spectrometers will increase data volumes by orders of magnitude, requiring automated detection of trace gas point sources. We present a fully automated framework that combines machine lear…
arXiv:2605.01482v1 Announce Type: new
Abstract: Multi-Hop Fact Verification (MHFV) necessitates complex reasoning across disparate evidence, posing significant challenges for Large Language Models (LLMs) which often suffer from hallucinations and frac…
arXiv:2505.20740v3 Announce Type: replace
Abstract: The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application in earth science-especially at the graduate level-r…
arXiv:2605.01507v1 Announce Type: new
Abstract: Prior studies report that partial driving automation can increase the cognitive demands on human drivers. This effect largely arises from human drivers’ lack of transparent insight into the vehicle’s int…
arXiv:2605.02187v1 Announce Type: cross
Abstract: Bring-Your-Own-Key (BYOK) agent architectures let users route LLM traffic through third-party relays, creating a critical integrity gap: a malicious relay can modify an aligned LLM response after gener…
arXiv:2605.01566v1 Announce Type: new
Abstract: Advances in inference methods have enabled language models to improve their predictions without additional training. These methods often prioritize raw performance over cost-effective compute usage. Howe…
arXiv:2605.03360v1 Announce Type: cross
Abstract: We present A-CODE, a fully atomic unified one-stage protein co-design model that simultaneously refines discrete atom types and continuous atom coordinates. Unlike predominant two-stage methods that ca…
arXiv:2605.03463v1 Announce Type: new
Abstract: Neural Surface Reconstruction has become a standard methodology for indoor 3D reconstruction, with Signed Distance Functions (SDFs) proving particularly effective for representing scene geometry. A varie…