#大语言模型
301 related articles
LLMs vs. TCM Physicians: Real Clinical Case Benchmarks Reveal AI's Promise and Risks
A study of 349 real TCM cases across 62 hospitals benchmarks 16 LLMs against 60 physicians. Top models outscored physicians on treatment principles but showed hallucinations and dosing errors in prescriptions.
The Hidden Bias in LLM Routing: Why Non-Standard English Users Get Downgraded Service
arXiv research reveals register bias in LLM complexity routing: queries in non-standard English and L2 English are systematically routed to weaker models due to input length signals, deepening AI inequity.
Relations Before Entities: The Deferred Commitment Mechanism in LLM Fact Recall
New arXiv research finds a temporal asymmetry in LLM fact recall: relation information becomes causally active 31–44% of network depth earlier than entity information, revealing a deferred commitment mechanism.
LLM-Extracted Features from Clinical Notes Improve Extubation Failure Prediction
UW Medicine researchers use LLMs to extract features from respiratory therapy notes, improving extubation failure prediction while exposing methodological inconsistencies across prior studies.
GraphEcho: Exposing the Evidence Redundancy Trap in LLM Graph Agents
GraphEcho benchmark reveals LLM graph agents mistake redundant paths for independent corroboration. New research evaluates PAPT's limits and the gap between efficient exploration and effective evidence use.
Breaking the 1.58-Bit Barrier: How Ternary LLMs Approach the Information-Theoretic Limit
Why 1.58-bit isn't the true lower bound for ternary LLMs. Learn how weight sparsity and entropy coding can break this information-theoretic barrier for efficient on-device deployment.
Fireworks Partners with Alibaba Cloud to Launch Qwen3 Flagship Models
Fireworks AI partners with Alibaba Cloud to bring the latest Qwen flagship models to its inference platform, letting developers build via API without managing GPU infrastructure.
One in Three AI Medical Records Has Errors: Omission Is the Deadliest Failure Mode
An audit of three AI medical scribes found one-third of notes had verifiable failures — mostly omissions. LLM judges are near coin-flip at detecting them. The fix: restructure the task.
Neuralese: When AI Thinks in a Language We Can't Read
AI safety researcher Rob Miles explains Neuralese, Chain of Thought, and opaque recurrence — why models may think in unreadable internal languages, and why CoT monitorability is a fragile safety window that's closing fast.
What Is Ollama? A Beginner's Guide to Deploying Open-Source LLMs Locally
Ollama is a free, open-source LLM management platform for locally deploying DeepSeek and other open-source models on macOS, Windows, Linux, and Docker — no API fees required.
RAG Framework for Intersection Safety: Using LLMs to Convert Crash Narratives into Countermeasure Recommendations
A new arXiv study proposes a RAG framework that uses LLMs to automatically convert intersection crash narratives into countermeasure recommendations, achieving an F1 score of 0.82 on real Florida data.
NepKANUN: A Deep Dive into Nepal's RAG-Based Legal AI Assistant
NepKANUN is a Nepali legal AI assistant built on RAG and fine-tuned LLMs, achieving BERTScore F1 up to 0.82 — a replicable blueprint for low-resource domain AI.
Survivorship Bias: The Overlooked Baseline Trap in LLM Research Idea Evaluation
An arXiv commentary reveals that LLM research idea evaluations suffer survivorship bias: human baselines use published papers while AI baselines use one-shot proposals, potentially making the observed gap a sampling artifact rather than a true capability difference.
Inference Networks: Optimizing LLM Inference Costs with Threshold Policies
A new arXiv paper proposes the Inference Networks graph framework for optimizing LLM inference costs, proving that optimal model activation follows a threshold structure for significant cost reduction.
DeepSeek Said It Was 'Sleepy' While Transcribing Music? Let's Talk About Anthropomorphism in LLM Chain-of-Thought
A Bilibili creator found DeepSeek saying it was 'sleepy' mid-task. We explain why LLMs mimic fatigue, how Chain of Thought amplifies anthropomorphism, and what to do about it.
Transformer Attention Mechanism Deep Dive: From Tokens to Self-Attention, Step by Step
A deep dive into the Transformer attention mechanism — from tokenization and embedding to Q/K/V self-attention, Mask, and Softmax — with step-by-step dimension tracking.
"Tokens Exhausted": The AI Anxiety Behind a Robot Video
A robot video called "Tokens Exhausted" went viral on Reddit, leaving viewers unable to tell if it was real Boston Dynamics footage. We unpack the AI satire and the anxieties it reflects.
PhysMent: Evaluating LLM Physical Reasoning with Interactive Physics Simulation
PhysMent is an interactive benchmark built on MuJoCo that evaluates LLM physical reasoning through tool-mediated experiments. Models excel at qualitative tasks but fail on quantitative multi-step ones — the bottleneck is procedural, not conceptual.
TimeThink: A Synthetic Framework for Teaching Temporal LLMs Compositional Reasoning
TimeThink is a synthetic framework for temporal LLMs that generates verifiable QA data using domain-agnostic time-series primitives and RLVR training, outperforming strong baselines on real-world benchmarks using only synthetic data.
Vibe Patenting: Can LLM Judges Reliably Evaluate Patent Drafting?
New arXiv research uses the Vibe Patenting platform to test LLM judges on patent drafting. Review-guided iteration boosts quality and can narrow the gap between low- and high-cost agents, but AI-human agreement is strongly metric-dependent.