4 Claude Skills Every Data Scientist Needs in 2026
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When to Use Claude Code and When to Use Codex
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RAG Is Not the Whole Toolkit: The NLP Techniques Real Problems Still Need
Enterprise Document Intelligence [Vol.1 #B00] - Retrieval answers one kind of question. Classifying a request, matching free text to a reference list, reading a table, cleaning OCR noise: each has a cheaper method that…
Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping
arXiv:2608.24135v2 Announce Type: replace Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) is pivotal for enhancing LLM code generation, yet its efficacy is often hindered by insufficient test case…
Can You Say This for Me? Speaking Up by Proxy in Co-Located Discussion
arXiv:2608.26185v1 Announce Type: new Abstract: Equal participation in co-located discussion is important for effective collaboration, yet people often hold back when they anticipate negative interpersonal or…
UniVVT: A Unified End-to-End Framework for High-Fidelity Video Virtual Try-on
arXiv:2608.05745v2 Announce Type: replace-cross Abstract: Video Virtual Try-On (VVT) synthesizes a video of a person wearing a target garment while preserving identity, motion, and scene dynamics. Dominant approaches…
Decay-Region Group Delay as a Forensic Cue for AI-Generated Impulsive Sounds
arXiv:2608.26346v1 Announce Type: cross Abstract: We investigate whether AI-generated impulsive sounds can be distinguished from real ones through group delay analysis. Our central finding is that AI-generated impulsive…
AI agents in Algorithmic Electricity Markets: On the Emergence of Tacit Collusion
arXiv:2608.26896v1 Announce Type: new Abstract: As electricity market participants increasingly adopt learning-based agents for their bidding strategies, electricity markets are becoming algorithmic. Evidence from…
MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation
arXiv:2604.20468v3 Announce Type: replace-cross Abstract: Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However, different…
A Safety-Gated Multimodal AI Backend for Mental-Health Support: Hierarchical State Representation, Conservative Risk Fusion, and Controlled Generation in Anian
arXiv:2608.26162v1 Announce Type: new Abstract: Safety-critical mental-health support systems must distinguish when supportive conversation is appropriate from when free-form generation should be blocked. This paper…
From Sound to Symptom: Real-Time Respiratory Signal Understanding for Conversational Healthcare Agents
arXiv:2608.26163v1 Announce Type: cross Abstract: Cough events during live spoken conversations carry clinically valuable respiratory signals, yet existing dialogue systems treat them as acoustic noise to be discarded.…
PACEShop: Evaluating Personalized, Actionable, Compositional, and Evidence-grounded Shopping Assistants
arXiv:2608.26180v1 Announce Type: cross Abstract: Shopping assistants are shifting from ranked product lists toward structured decision support, where systems must synthesize shopper context, product evidence, and…
CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models
arXiv:2601.04778v2 Announce Type: replace-cross Abstract: Video-language models (VLMs) achieve strong multimodal understanding but remain prone to hallucinations, especially when reasoning about actions and temporal…
Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics
arXiv:2508.11017v3 Announce Type: replace-cross Abstract: Large language models (LLMs) struggle with cross-lingual knowledge transfer: they sometimes hallucinate when asked in one language about facts expressed in a…
LLM-Specific Utility for Retrieval-Augmented Generation
arXiv:2510.11358v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) is typically optimized for topical relevance, yet its success ultimately depends on whether retrieved passages are useful…
DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping
arXiv:2510.12979v2 Announce Type: replace Abstract: Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to tackle complex…
ADeptS-Bench: Measuring the Trustworthiness of Computer Use Agents Across Devices
arXiv:2608.26204v1 Announce Type: cross Abstract: Computer Use Agents (CUAs) are increasingly deployed to navigate mobile and desktop applications on behalf of users, yet no benchmark comprehensively evaluates whether…
Evaluating AI Generated Summaries for Cancer Patients
arXiv:2608.26154v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into digital health platforms to generate summaries of complex medical data. Although these models can…
CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases
arXiv:2608.27391v1 Announce Type: new Abstract: LLMs are increasingly able to answer complex questions about enterprise-scale document collections. But evaluation is hard: companies don't want to share internal…
Decoupling Planning and Control for Instructable Agents
arXiv:2608.26788v1 Announce Type: new Abstract: Recent work shows that pre-trained, instruction-tuned vision-language models (VLMs) perform well at mapping from instructions and observations to high-level plans, but…
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