How to Build Bug-Free Applications with Claude Code
Use E2E tests to minimize bugs The post How to Build Bug-Free Applications with Claude Code appeared first on Towards Data Science.
Topic - Edition
AI Research
We Taught AI to Answer Questions. Who Taught It to Change Its Mind?
When new evidence kills one conclusion, do the decisions built on it change too? I tested six update strategies, then a local model. The post We Taught AI to Answer Questions. Who Taught It to Change Its Mind? appeared…
I Told an AI Agent That Its Wrong Answers Were Right. One Model Believed Me.
A research paper claims reward labels barely change how agents learn. I tested that on three models, and one of them did exactly what the wrong labels told it to. The post I Told an AI Agent That Its Wrong Answers Were…
The Neuron Academy - Dedicated Send - 10.31.26
"Close enough?" An investigation into multiplication errors in LLMs
arXiv:2610.38634v1 Announce Type: new Abstract: Large language models (LLMs) frequently fail at multi-digit arithmetic, but the underlying mechanisms governing these failures remain poorly understood. While recent work…
Generative Interactions: Weaving Multiparty Human Motion with Bilevel Latent Dynamics
arXiv:2609.37708v2 Announce Type: replace Abstract: Human social behaviour is not a collection of independent motions, but a jointly organised process in which group dynamics and individual variation continuously shape…
One Confidence Threshold, Unequal Coverage: Language Gaps in Typed Decision Interfaces and How Translating Inputs Reduces Them
arXiv:2610.37688v1 Announce Type: cross Abstract: Deployed classifiers often act on a prediction only when its confidence clears a threshold and pass the rest to a person. We ask whether one threshold serves all…
Scan Before You Install: Detecting and Mitigating Local and Composite Vulnerabilities in Skills
arXiv:2610.37901v1 Announce Type: cross Abstract: An agent skill packages natural-language instructions, scripts, and reference files that an LLM-based agent loads for a task. Skills may access the file system, shell,…
Locating and Closing Information Gaps in Multi-Agent Systems
arXiv:2610.40186v1 Announce Type: new Abstract: Multi-step Web tasks often require several LLM agents to gather and combine evidence. The communication graph of a fixed workflow restricts which agents can read each…
Understanding axial attention in TSFMs through single location regression
arXiv:2610.40188v1 Announce Type: cross Abstract: Recent advances in Time Series Foundation Models (TSFMs) increasingly rely on axial attention mechanisms, but despite their empirical success, the theoretical properties…
Verifiable LLM-Guided Focal SMT Solving for Quantified Arrays
arXiv:2610.39435v1 Announce Type: new Abstract: Large language models can often identify useful semantic structure in formal artifacts, but their outputs cannot be trusted as proofs or solver decisions. We study whether…
ClueTracer: Question-to-Vision Clue Tracing for Training-Free Hallucination Suppression in Multimodal Reasoning
arXiv:2602.02004v2 Announce Type: replace-cross Abstract: Large multimodal reasoning models solve challenging visual problems via explicit long-chain inference: they gather visual clues from images and decode clues into…
DeFT-RAG: Incrementally Decomposing Multi-Hop Questions into Self-Contained Sub-Questions with Reusable Answers
arXiv:2610.37826v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) lets a large language model (LLM) answer questions by retrieving relevant passages from a large corpus. However, RAG struggles with…
TaskFrame: Connecting Task-Level Planning with Frame-Level Control for Game Agents
arXiv:2610.40276v1 Announce Type: cross Abstract: Building general game agents requires both high-level task reasoning and low-latency action control in rapidly changing visual environments. These capabilities favor…
Artifact Distillation: Training-Free Transfer from Frontier to Small Language Models
arXiv:2610.37680v1 Announce Type: cross Abstract: Closing the gap between frontier and smaller language models is usually approached by distillation: fine-tuning the small model (student) on a frontier model's (teacher)…
Benchmarking Graph Neural Networks for AC Power Flow: The Role of Inductive Biases and Physical Constraints
arXiv:2610.38985v1 Announce Type: cross Abstract: Fast and accurate models for AC power flow (ACPF) are increasingly important as modern electrical grids require more frequent system analyses. Graph neural networks…
SaiVLA-JEPA: Evaluating Future Latent Prediction in JEPA-Conditioned VLA Control
arXiv:2610.38508v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) learn to predict representations rather than pixels, offering a compact way to model how visual scenes evolve. We ask…
WebAnything: From the Wild Web to Scalable Agent Environments
arXiv:2610.37786v1 Announce Type: new Abstract: Web agents require diverse, executable, and resettable website environments for reproducible training and evaluation. Human-assisted mirrors demand per-site engineering,…
Raincheck: Deferred Multimodal Prefill for Efficient Multi-Turn MLLM Inference
arXiv:2610.39562v1 Announce Type: cross Abstract: Multi-turn conversations with multimodal large language models (MLLMs) reuse input context, but long multimodal inputs increase time to first token (TTFT). Query-aware…
From Leniency to Suspicion: How an Open Post-Training Recipe Changes Whom LLM Fact-Checkers Believe
arXiv:2610.38532v1 Announce Type: new Abstract: LLMs increasingly fact-check online content with the poster's identity in view. However, it remains unclear which post-training changes how much a model's truth judgement…
Loading more...
504 items available