Human-in-the-Loop Without Killing Throughput
How we stopped reviewing every agent action and started routing human attention where it actually mattered The post Human-in-the-Loop Without Killing Throughput appeared first on Towards Data Science.
Daily edition · AI Research
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440 articles · 3 sources · 440 papers ·
Top topics: AI Research · AI · Python
From One Agent to a Team: Understanding Codex Subagents
A hands-on guide to defining specialist agents and coordinating their work in the Codex CLI The post From One Agent to a Team: Understanding Codex Subagents appeared first on Towards Data Science.
Connecting My LangGraph AI Agent to Postgres
How to run the backend locally with Docker or in the cloud The post Connecting My LangGraph AI Agent to Postgres appeared first on Towards Data Science.
Why Claude Code Time Estimates Are Poor
Be a better communicator with LLM programming The post Why Claude Code Time Estimates Are Poor appeared first on Towards Data Science.
TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping
arXiv:2604.21057v2 Announce Type: replace Abstract: The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling LRMs to reason…
VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation
arXiv:2608.26155v1 Announce Type: new Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limited by the scarcity…
MAPLE: Metadata Conditioned LLM Pretraining for Locale-Aware Question Answering
arXiv:2601.15236v2 Announce Type: replace Abstract: Large language models can memorize competing locale-specific facts yet fail to select among them when the locale changes, defaulting instead to a single globally…
The Limits of Automatic Evaluation of Creativity in Large Language Models
arXiv:2608.23705v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly capable of generating text that challenges human performance in domains requiring creativity, yet evaluating creativity…
ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions
arXiv:2605.24279v2 Announce Type: replace Abstract: A frontier language model's acknowledged "helpful programming assistant" persona does not survive long agentic-coding sessions in the deployment regime that production…
Summarization is Not Dead Yet
arXiv:2606.08000v2 Announce Type: replace Abstract: The progress of large language models (LLMs) has fueled claims that model-generated summaries rival or even surpass human-written references, raising questions about…
Training Agents to Evolve with Their Harness: TaoLive Digital Avatar Agent Technical Report
arXiv:2608.15763v3 Announce Type: replace Abstract: AI-powered digital avatar streamers must answer product questions, engage viewers, and execute marketing strategies in real time, demanding low latency, frequent…
Reasoning about In-Context Samples for Machine-Translation
arXiv:2608.27036v1 Announce Type: new Abstract: Large Language Models (LLMs) can be trained to perform chain-of-thoughts reasoning in order to improve the reliability of their responses. In this work, we investigate how…
Investigating the Influence of Prompt and Response Languages on LLM Content Generation
arXiv:2608.26186v1 Announce Type: new Abstract: This study examines how prompt and response language influence the behavior of large language models. Using five models, we evaluated answers to 68 non translation…
SWE-Prime: Fewer Trajectories, Better Performance
arXiv:2608.27449v1 Announce Type: cross Abstract: To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory datasets and…
Survival-Guided Length Control for Efficient Diffusion Language Models
arXiv:2608.26374v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or relies on ad hoc…
An Embarrassingly Simple Detector for Model Extraction Attacks in Large Language Model API Traffic
arXiv:2606.05725v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed through hosted APIs, making model extraction a practical threat to model ownership and service security.…
Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning
arXiv:2509.03345v3 Announce Type: replace-cross Abstract: Non-deductive reasoning, encompassing inductive and abductive reasoning, is essential in addressing complex real-world questions. One key feature of inductive…
Research Design Tracking and Assessment for the Social Sciences
arXiv:2608.27049v1 Announce Type: new Abstract: Reliable assessment of causal research designs in the social sciences is critical for evidence-based policy-making, yet has so far relied entirely on manual expert…
Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performance
arXiv:2608.26480v1 Announce Type: cross Abstract: Multi-agent large language model systems are widely reported to beat single-model baselines, but the evidence is mixed, and comparisons are usually confounded: pipelines…
Preserving General Capabilities during Domain Specialization with Uncertainty-Calibrated MOPD
arXiv:2608.26735v1 Announce Type: new Abstract: Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities such as reasoning, coding, instruction…
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