The Archive

Spotify CTO demonstrates Claude integration for automated podcast generation stored in user libraries.

AutoTTS framework uses agentic discovery to automatically design test-time scaling strategies for LLMs rather than hand-crafting heuristics.

Normalizing Trajectory Models combines invertible flows with likelihood training for few-step generative sampling without distillation.

Conformal Path Reasoning applies statistical conformal prediction to knowledge graph QA with calibrated coverage guarantees.

Pipeline decodes imagined speech from brain MEG recordings by leveraging paired listened-speech data from musicians.

GRAPHLCP integrates graph topology into localized conformal prediction for GNNs with improved calibration and set efficiency.

EmambaIR applies state space models to event-based image reconstruction with linear complexity versus quadratic ViT alternatives.

Theoretical analysis of non-negative L₁-approximating polynomials for Gaussian distributions with applications to learning theory.

VecCISC improves test-time scaling via reasoning trace clustering and selective critic calls versus full Confidence-Informed Self-Consistency.

Flow-OPD applies on-policy distillation to Flow Matching text-to-image models to reduce reward hacking and multi-task interference.

Rubric-grounded RL decomposes rewards into verifiable criteria scored by frozen LLM judges for generalizable multi-criterion reasoning optimization.

Study shows expanded context windows degrade multi-agent cooperation in LLMs across 7 models; mechanism is eroding forward-looking intent rather than increased distrust.

Reddit post with no substantive content; appears to be social media chatter without technical details or news.

CA-SQL improves Text-to-SQL performance on BIRD benchmark via complexity-aware inference-time reasoning with dynamic exploration budgets.

Principled Q-value algorithms for exponential-utility RL in discounted MDPs with convergence guarantees via contraction operators.

Statistical method for measuring semantic breadth of words using contextualized embeddings; addresses confounding factors in hypothesis testing.

CMR-EXTR extracts structured data from free-text cardiac MRI reports using distilled LLMs with uncertainty quantification for clinical quality control.

Byte Latent Transformer (BLT) accelerates byte-level LM inference via diffusion-based multi-byte parallel generation without subword vocabularies.

Link: hacks.mozilla.org

SCOPE framework orchestrates modular skills for faithful complex image generation by tracking semantic commitments across grounding, generation, and verification.

GraphDPO extends Direct Preference Optimization to preference graphs from multi-rollout data, avoiding DPO's pairwise data collapse and conflicting supervision.

Reddit post title mentions Claude and Microsoft partnership; insufficient detail to assess business/technical significance.

CUTS-GPR enables high-dimensional Gaussian process regression with near-linear scaling via additive kernels on incomplete grids.

PropSplat reconstructs RF propagation fields using 3D anisotropic Gaussians without maps or dense measurement campaigns.

Proposes DR-ME, a semiparametrically efficient test for detecting distributional treatment effects beyond means in causal inference.

You can stop Chrome from taking up 4GB of storage for local AI, but that shouldn't be your problem.

Test-time domain adaptation framework for PET image reconstruction generalizing from phantom to clinical data.

STARFlow2 unifies text-image generation via autoregressive normalizing flows, aligning causal masking with LLM architecture.

ADD-PINN applies domain decomposition to physics-informed neural networks for traffic flow estimation with sparse sensors.