PExA: Parallel Exploration Agent for Complex Text-to-SQL
arXiv:2604.22934v1 Announce Type: new
Abstract: LLM-based agents for text-to-SQL often struggle with latency-performance trade-off, where performance improvements come at the cost of latency or vice versa. We reformulate text-to-SQL generation within the lens of software test coverage where the ori...
The Power of Power Law: Asymmetry Enables Compositional Reasoning
arXiv:2604.22951v1 Announce Type: new
Abstract: Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggests that reweighting or curating data towards a uniform distribution may help models better learn the...
On the Existence of an Inverse Solution for Preference-Based Reductions in Argumentation
arXiv:2604.22958v1 Announce Type: new
Abstract: Preference-based argumentation frameworks (PAFs) extend Dung's approach to abstract argumentation (AAFs) by encoding preferences over arguments. Such preferences control the transformation of attacks into defeats, and different approaches to doing so ...
Towards Causally Interpretable Wi-Fi CSI-Based Human Activity Recognition with Discrete Latent Compression and LTL Rule Extraction
arXiv:2604.22979v1 Announce Type: new
Abstract: We address Human Activity Recognition (HAR) utilizing Wi-Fi Channel State Information (CSI) under the joint requirements of causal interpretability, symbolic controllability, and direct operation on high-dimensional raw signals. Deep neural models ach...
Meet Talkie-1930: A 13B Open-Weight LLM Trained on Pre-1931 English Text for Historical Reasoning and Generalization Research
What if a language model had never heard of the internet, smartphones, or even World War II? That’s not a hypothetical — it’s exactly what a team of researchers led by Nick Levine, David Duvenaud, and Alec Radford has built. They call it talkie, and it may be the most historically disciplined large ...
StereoFoley: Object-Aware Stereo Audio Generation from Video
We present StereoFoley, a video-to-audio generation framework that produces semantically aligned, temporally synchronized, and spatially accurate stereo sound at 48 kHz. While recent generative video-to-audio models achieve strong semantic and temporal fidelity, they largely remain limited to mono o...
Local Mechanisms of Compositional Generalization in Conditional Diffusion
Conditional diffusion models appear capable of compositional generalization, i.e., generating convincing samples for out-of-distribution combinations of conditioners, but the mechanisms underlying this ability remain unclear. To make this concrete, we study length generalization, the ability to gene...
Learn how OpenAI protects community safety in ChatGPT through model safeguards, misuse detection, policy enforcement, and collaboration with safety experts.
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM’s autoregressive decoding may limit the ability to revisit and refine earlier tokens in a holistic manner, which can also lead to inefficient exploration for diverse solutions. In...
Build a Reinforcement Learning Powered Agent that Learns to Retrieve Relevant Long-Term Memories for Accurate LLM Question Answering
In this tutorial, we build a Reinforcement Learning–driven agent that learns how to retrieve relevant memories from a long-term memory bank. We start by constructing a synthetic memory dataset and generating queries that require the agent to recall specific information. Using OpenAI embeddings, we c...
OpenMOSS Releases MOSS-Audio: An Open-Source Foundation Model for Speech, Sound, Music, and Time-Aware Audio Reasoning
The model unifies speech, environmental sound, music, and temporal reasoning into a single architecture — and outperforms every open-source model tested on general audio benchmarks, including systems more than four times its size.
The post OpenMOSS Releases MOSS-Audio: An Open-Source Foundation Mode...
DeepMind’s David Silver just raised $1.1B to build an AI that learns without human data
Ineffable Intelligence, a British AI lab founded a mere few months ago by former DeepMind researcher David Silver, has raised $1.1 billion in funding at a valuation of $5.1 billion.
How Spreadsheets Quietly Cost Supply Chains Millions
A simulation of how a single forecast change moves through five planning teams, and why most retailers lose money in the gap between Sales and Stores.
The post How Spreadsheets Quietly Cost Supply Chains Millions appeared first on Towards Data Science.
OpenAI is available at FedRAMP Moderate authorization for ChatGPT Enterprise and the OpenAI API, enabling secure AI adoption for U.S. federal agencies.
Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data. While consumer-facing AI tools have dazzled users with speed and ease, enterprise leaders are discovering that deploying AI a...
Comparing Explicit Measures to Calculation Groups in Tabular Models
With the advent of UDFs and their combination with calculation groups, I see a lot of discussion about not creating explicit measures but instead offering calculation groups to report creators.
The post Comparing Explicit Measures to Calculation Groups in Tabular Models appeared first on Towards Dat...
Show Your Work: The Case for Radical AI Transparency
A colleague told me something recently that I keep thinking about. She said, unprompted, that she appreciated seeing both sides of my AI conversations. Not just the output. The full thread. My prompts, the AI’s responses, the back and forth, the dead ends, the iterations. She said it made her trust ...