AI Research

Your Agent Doesn't Need More Freedom

Agents got good. The hard part now is everything around them. The post Your Agent Doesn't Need More Freedom appeared first on Towards Data Science.

Q4 TNA Email - Muse

Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

Benchmarking NumPyro, affine-invariant MCMC, and dynesty against exact ground truth and watching them fail. The post Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling appeared first on Towards Data…

Coding Agents Can Solve the Task — But How Much Work Did They Waste?

Real repositories, seeded agent decisions: what 50,400 runs show about wasted turns, patch churn, and which harness rules help The post Coding Agents Can Solve the Task — But How Much Work Did They Waste? appeared first…

Google’s Playground Turns Prompts Into Games. Can It Build an Audience?

Google’s Playground lets people create playable games through text prompts, with Unity Spark set to add more advanced tools. The partnership’s next challenge is helping creators refine their games and reach players who…

How to Leverage NLP for Product Data Science

A practical guide to strengthening churn, CLV, and other traditional models with text The post How to Leverage NLP for Product Data Science appeared first on Towards Data Science.

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AMD’s Helion Could Change the Cost of Running AI Agents

AMD’s Helion combines configurable CPU and GPU racks with model routing to address the computing demands of AI agents. Its potential savings depend on deployment costs and real-world performance.

PreSTO: Predictive Subtree Prefetching for Fast LLM Power Sampling

arXiv:2610.13171v1 Announce Type: new Abstract: Power sampling improves large language model (LLM) reasoning at test time by sampling from a sharpened version of the base model's distribution. Its sampler, PowerMH, is…

BenCoDiC: A Large-Scale Contextual Cyberbullying Corpus for Bengali Political News Discourse FULL VERSION

arXiv:2610.13121v1 Announce Type: new Abstract: Cyberbullying is a growing concern in online communities, yet existing Bengali corpora remain limited in contextual information, annotation transparency, scale,…

Revisiting Accent Classification with DistilHuBERT: Speaker-Disjoint Evaluation and Cross-Corpus Generalization

arXiv:2610.13440v1 Announce Type: cross Abstract: Recent accent classification systems can achieve high accuracy in standard in-corpus evaluations. However, when speakers overlap between the training and test sets, such…

O\'ido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present O\'ido, an inference engine that…

CAST: Credit Alignment for Cross-Tokenizer On-Policy Distillation

arXiv:2610.13257v1 Announce Type: cross Abstract: Cross-tokenizer on-policy distillation (OPD) requires aligning teacher and student sequences before their scores can be compared. Decoded-text alignment provides such…

From 2.1M Hours of Raw Broadcast Audio to Finnish Speech SSL: Confidence Filtering and Architectural Analysis at Scale

arXiv:2610.13102v1 Announce Type: new Abstract: Broadcast archives offer scale and diversity for self-supervised learning (SSL) but contain substantial noisy, non-speech, and multilingual content. Prior work typically…

Test-Time Memory Construction

arXiv:2610.13348v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to answer questions over long interaction histories, where relevant evidence may be scattered across distant sessions. Existing…

A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs

arXiv:2610.02529v2 Announce Type: replace Abstract: Syntactic ambiguity poses a persistent challenge for Arabic NLP, particularly in morphologically rich nominal constructions where multiple structu6ral interpretations…

Knowing When to Stop: Efficient Context Processing via Latent Sufficiency Signals

arXiv:2502.01025v4 Announce Type: replace Abstract: Large language models (LLMs) process entire input contexts indiscriminately, which is inefficient when the information required to answer a query is localized within…

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is challenging, as…

ARTIS: Agentic Risk-Aware Test-Time Scaling via Iterative Simulation

arXiv:2602.01709v3 Announce Type: replace Abstract: Current test-time scaling (TTS) techniques enhance large language model (LLM) performance by allocating additional computation at inference time, yet they remain…

When LLMs Sit Above Diagnostic Tools: Unrealized Complementarity in Industrial Fault Diagnosis

arXiv:2610.05031v2 Announce Type: replace Abstract: Large language models are increasingly used as integration layers above specialized tools, but a stronger component does not necessarily produce a stronger combined…