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.
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AI Research
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.
😺 Meta’s Muse Wonder is here, priced like Opus
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.
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…
SOAR: Source-Aware Reinforcement Learning with Precise Credit Assignment for Search Agents
arXiv:2610.13157v1 Announce Type: new Abstract: Reinforcement learning (RL) for search agents often suffers from evidence fabrication, a failure mode where agents bypass external information ($E_{ext}$) and fabricate an…
Towards Enriching Design-Time Models with Evidence from Simulation and Operational Activities
arXiv:2610.13456v1 Announce Type: new Abstract: Cyber-Physical Systems are developed through multiple model based activities, comprising several stages of development. As the development progresses through simulation,…
Smoothing the Top-k Exposure Boundary for Sparse Mixture-of-Experts
arXiv:2610.11575v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts models scale parameter capacity efficiently while maintaining a fixed compute budget per token. However, traditional training paradigms…
A Better Metric Will Not Save You: What You Compare Beats How You Compare It
arXiv:2610.13476v1 Announce Type: new Abstract: Representational similarity measures (RSA, CKA, Procrustes) are chosen for the transformations they treat as irrelevant, and all of them take the set of conditions as…
Evo$^2$: Evolving the Evolver through Weight-Harness Co-Evolution
arXiv:2610.13025v1 Announce Type: new Abstract: Self-evolving agents are increasingly used to improve language model systems without human intervention through either weight updates or harness improvements. Existing…
Evaluating LLM Creativity through Long-Tail Performance
arXiv:2610.12998v1 Announce Type: new Abstract: Creativity benchmarks for large language models (LLMs) vary widely in task and metric design. This raises the question of whether they capture a common notion of…
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…
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