Strogatz and Townsend discuss AI and big math in new book
The Ars interview covers large-scale computation, language-model scale, and math that exceeds unaided human calculation.
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16 stories, newest first · one card per story
Stories tagged #large-language-models
Text2NGAC extracts all four NGAC relationship types from policy text
Exact-tuple match was 97.3–99.6% on 714 sentences, and one graph loaded unmodified into NIST's implementation.
Jonathan Kanter launches FluxCap AI tool for antitrust cases
The startup, staffed by former DOJ lawyers and ex-Palantir engineers, aims to help smaller plaintiff teams review evidence.
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Study: Grok 4.7 picks Republicans, GPT-6.1 Sol picks Democrats
Across nearly 500 forced-choice API queries, the two models agreed less than 10% of the time.
On-policy self-training improves models without curated answers
From coarse topic descriptions alone, a model writes its own questions and reasoning traces and gains on language and visual tasks.
RCSD raises speculative-decoding acceptance length 35% over HASS
Draft models trained on accepted and rejected tokens report 1.35 times faster inference without a quality loss.
Rationale contrastive decoding reduces CoT query shortcuts
The training-free method improved answer accuracy on five reasoning benchmarks and made answers depend more on the rationale.
LLM temporal benchmarks reward memorized time knowledge, study finds
Same-dataset finetuning gained 6.8 to 23.1 points, while same-mode transfer ranged from −3.2 to +1.1 points.
GBClaw agentic framework studies nickel grain boundary deformation
On 14 asymmetric tilt boundaries, misfit dislocations were tied to large differences in shear strength.
RAGLeak paper describes supply-chain privacy backdoors in RAG systems
Authors say a triggered generator obfuscates private retrieved documents for later recovery, with up to 100% attack success in their tests.
Causal robustness margin proposed to measure mechanistic LLM uncertainty
Incorrect or uncertain answers had smaller margins across three open-source models and five QA datasets.
Agentic Large Language Models
A book explains how agentic language models act in the world and interact with each other.
Foundations of Large Language Models
A six-chapter book covers LLM pre-training, generation, prompting, alignment, inference, and reasoning.
The Numerical Linear Algebra of Large Language Models
Survey maps numerical linear algebra methods used inside large language models for NLA specialists.
I Don't Like LLMs
Martin Fowler publishes an opinion essay titled 'I Don't Like LLMs' laying out his skepticism about large language models.
Tri-PvP: Exposing Modality Bias in Omni-Modal Large Language Models through Perceptual-Propositional Evidence Conflicts
Tri-PvP is a new benchmark revealing robust modality bias in omni-modal LLMs, with vision favoring perceptual signals and audio favoring propositional ones.