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343 articles · 5 sources · 342 papers ·
Top topics: AI · AI Research · Python
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Your LLM Can Return Perfect JSON and Still Be Wrong
What I learned after thinking more carefully about Structured Outputs on messy, incomplete data The post Your LLM Can Return Perfect JSON and Still Be Wrong appeared first on Towards Data Science.
FAQ as RAG: When You Get to Design the Corpus
Enterprise Document Intelligence [Vol.1 #B2] - The FAQ inverts every brick of the standard RAG pipeline. Parsing is trivial, retrieval doubles as a cache, and few-shot prompting becomes a retrieval problem too The post…
Why RAG Complexity Should Be Earned
A framework for building RAG pipelines that introduces complexity in response to observed failure modes, from lexical and hybrid search to reranking and agentic information seeking The post Why RAG Complexity Should Be…
AgentOps Is Not MLOps: What Breaks in Your Monitoring Stack When Agents Go to Production
The five MLOps monitoring assumptions agents break, and which inherited signals now pass failed runs as healthy. The post AgentOps Is Not MLOps: What Breaks in Your Monitoring Stack When Agents Go to Production appeared…
PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems
arXiv:2608.28378v1 Announce Type: new Abstract: Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally complete, single-turn…
Cognitive Chain-of-Thought (CoCoT): Structured Multimodal Reasoning about Social Situations
arXiv:2507.20409v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting helps models think step by step. But naive CoT breaks down in visually grounded social tasks, where models must perceive, understand,…
SimpCue: Cue-Based Prompting for Multilingual Text Simplification
arXiv:2608.28042v1 Announce Type: new Abstract: Text simplification aims to make complex texts easier to understand while preserving their original meaning. Recent large language models can perform simplification…
MemoryCard: Topic-Aware Multi-Modal Clue Compression for Long-Video Question Answering
arXiv:2606.05917v2 Announce Type: replace-cross Abstract: Long-video question answering remains challenging for Vision-Language Models (VLMs), as answer-relevant evidence is often sparse, transient, and temporally…
Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL
arXiv:2608.28432v1 Announce Type: new Abstract: Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly elaborate pipelines…
Steering Multimodal Large Language Models Decoding for Context-Aware Safety
arXiv:2509.19212v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisions remains…
DisCTI: Who Needs to Know Timely? Automated Sector-Aware Cyber Threat Intelligence Dissemination
arXiv:2608.27967v1 Announce Type: cross Abstract: The timely dissemination of cyber threat intelligence (CTI) is critical for organizations to mount swift and effective incident response. When valid CTI is delivered to…
Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs
arXiv:2608.28383v1 Announce Type: cross Abstract: Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on why certain attention…
Semantic Watermarking with Order-Robust Detection over Sub-sentence Units
arXiv:2608.27666v1 Announce Type: cross Abstract: Semantic watermarks tie the mark to sentence meaning rather than token choices, promising robustness to content-preserving edits. However, the detector only observes…
ProfileFoundry: A Synthetic Person-Object Substrate for Privacy, Memory, and Tool-Use Evaluation in LLM Agent
arXiv:2606.26403v2 Announce Type: replace Abstract: Foundation-model research increasingly needs data about people: user state, personal histories, relationships, contact-like fields, documents, and longitudinal…
PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection
arXiv:2502.12119v5 Announce Type: replace-cross Abstract: Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications. However, the…
Auditing Generative Audio Calls for Known-Task Audio-LLM Evaluation
arXiv:2608.27817v1 Announce Type: cross Abstract: Speech and audio LLMs are often evaluated by asking whether a waveform prompt beats an automatic speech recognition (ASR) transcript. For known closed-set tasks, that…
Does Finetuning with Scientific Data Increase Hallucinations? A Multi-domain Factuality Evaluation of LLMs
arXiv:2606.21359v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet their tendency to hallucinate poses significant risks in this…
Select, Don't Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection
arXiv:2608.27470v1 Announce Type: new Abstract: Entity Disambiguation (ED) is a key task for constructing and using knowledge graphs. State-of-the-art neural approaches commonly model ED as a single task, although it…
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