Song
Song — researcher or builder tracked in the Angestrom contributor network.
News · 5
'Music brings everyone together' - Docker River Band reflects on Guts Touring 2026 - National Indigenous Times
<a href="https://news.google.com/rss/articles/CBMitAFBVV95cUxPNnRPMHpnc1BCNTQxTC15TjE2VTdqSG85T1AwS1BwU2ZocEthd0d4VEp0b2RRYzNuWWNLYWdRazlaNWE0RHhSeFR5Q0U4Q1JKNnF5LV82bklOX2JMU05NUTFyWmVzTkRYR1VEWkVMXzRGbm5jN1JtWVJxTVp0TzVpQTdjSmJJMjU4Wm1Hem9ZLUIwZFNCU2xja3RBR3BmcnM2MWZFMWpjdWxvZWxPTzc4RFduclM?oc=5" target="_blank">'Music brings everyone together' - Docker River Band reflects on Guts Touring 2026</a> <font color="#6f6f6f">National Indigenous Times</font>
Here are the 30,000 songs Sony is suing Udio’s AI music generator over
Sony Music Entertainment has filed another lawsuit against Udio, accusing the AI music generator of infringing the copyright of more than 30,000 of its songs, ranging from Elvis Presley's Hound Dog to Beyoncé's Say My Name, and Harry Styles' As It Was. The lawsuit, filed in a New York court on Monday, claims that this […]
Zhu Songchun: China's AI Industry Should Not Be Misled by the "Musk Belief" - 36 Kr
<a href="https://news.google.com/rss/articles/CBMiU0FVX3lxTE1YcmlXZVl6a3poREVxaHpCRDM1MDAzVjRjV1FxMFVTUzdpc2haVzRvd2Zhb3JMME42NV9DNTNkLVZrM0Roeno0Zi00aHR5bkMwalow?oc=5" target="_blank">Zhu Songchun: China's AI Industry Should Not Be Misled by the "Musk Belief"</a> <font color="#6f6f6f">36 Kr</font>
Meta launched a new AI optimism ad set to a song about human extinction
David Bowie's song "Five Years," which Meta used in a supposedly inspiring advertisement, is about humans learning that they have five years left to live before the apocalypse.
Meta’s New Feel-Good AI Ad Uses a Song About the World Ending
The clip features the David Bowie track “Five Years,” which includes lyrics such as “Earth was really dying (dying).”
Papers · 3
Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-ordering a candidate list, but they are slow at inference: an autoregressive (AR) decoder spends one sequential forward pass per reasoning token, and the reasoning trace far exceeds the ranking it produces. To reduce this cost, block-diffusion language models decode many positions in parallel over a few denoising steps and are substantially faster, yet naively converting an AR re-ranker into one opens two accuracy gaps: (1) a structural gap: answer positions are denoised in parallel
Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering
In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and musical attributes. The proposed framework supports three tasks: Lyrics-to-Song Generation, which generates complete songs from text descriptions, lyrics, and musical attributes; Instrumental Music Generation, which creates music without vocals; and Cover Song Generation, which reinterprets existing songs with different styles while preserving their melodic content. Architecturally, our system consists of four main components: a semantic-aware t
A Hybrid Framework for Song Lyric Annotation Based on Human-LLM Alignment
Emotion recognition of song lyrics is a challenging task since lyrics may not necessarily align with the overall emotion of a song. As a result, lyrics annotation remains largely underexplored. Drawing inspiration from research in large language model (LLM) assisted annotation, we examine the alignment between humans and LLMs for annotation of lyrics by creating a new sentence-level dataset of lyrics. Our observations highlight the subjectivity of the task and the inherent challenges. Following this, we present a hybrid annotation framework that optimizes human and LLM annotation by predicting
Repositories · 2
YuanpingSong/ultracodex
Run Claude Code workflow scripts, unmodified, on the OpenAI Codex CLI — fable plans, codex executes, fable verifies. Parallel agent fleets, builder–verifier loops, token budgets, full-screen TUI.
V-Songbird/hush
🤫 Token-lean sessions at the harness level. An easy to grasp output style, output-shrinking hooks, and log compression cut both input and output tokens.