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small language model

3,200 papers

#small language model Open access Sep 2026

What Sets the Speed Is the Power, Not the Gear ── 200 W balances at 32.13 km/h, far above the 13.46 km/h a 34x28 reaches ── what a gear selects is not speed but cadence ── reaching 25 km/h in 34x28 demands 167.2 rpm ── [Paper 449]

A low gear is slow and a high gear is fast──so it is thought. This paper shows that power sets the speed and the gear only selects the cadence──so “a lower gear makes you slower” is true only when the power drops. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──gear...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

White Is Made by a Difference, Not by a Colour ── The same "white powders" scatter as 1 to 0.006944 once mixed into a resin, a factor of 144 ── wet the paper and the difference falls from 1.70 to 1.37, taking 35.1 per cent of the scattering with it ── match the index and the white vanishes exactly ── [Paper 442]

A white powder is taken to be white. This paper shows that whiteness is not a property of the powder──it is made by the difference from its surroundings, and vanishes when the difference does. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──light scattering, hiding...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

What Sets the Speed Is the Power, Not the Gear ── 200 W balances at 32.13 km/h, far above the 13.46 km/h a 34x28 reaches ── what a gear selects is not speed but cadence ── reaching 25 km/h in 34x28 demands 167.2 rpm ── [Paper 449]

A low gear is slow and a high gear is fast──so it is thought. This paper shows that power sets the speed and the gear only selects the cadence──so “a lower gear makes you slower” is true only when the power drops. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──gear...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

The Water Load Grows as the Square, and the Dam Only as the First Power ── Ten times the depth multiplies the resultant thrust by 100 and the overturning moment by 1000 ── yet the required width only doubles ── 18.6339 m at H=50, 37.2678 at H=100, with b/H constant at 0.3727 ── [Paper 454]

A deeper dam is thought to need a disproportionately thicker body. This paper shows that although the force grows as the square and the moment as the cube, the required width grows only as the first power──because the resisting side grows as the cube too. No new theorem or law is claimed. Scope of this paper (scope not...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

White Is Made by a Difference, Not by a Colour ── The same "white powders" scatter as 1 to 0.006944 once mixed into a resin, a factor of 144 ── wet the paper and the difference falls from 1.70 to 1.37, taking 35.1 per cent of the scattering with it ── match the index and the white vanishes exactly ── [Paper 442]

A white powder is taken to be white. This paper shows that whiteness is not a property of the powder──it is made by the difference from its surroundings, and vanishes when the difference does. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──light scattering, hiding...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

The Metal That Reacts Most Readily Is the One That Does Not Corrode ── Aluminium sits at -1.66 V, baser than iron, yet its film is 4 nm, 1/125 of iron's 500 nm ── the ordering is reversed ── what separates them is not the potential but whether the film can cover what lies beneath ── [Paper 441]

A metal that reacts more readily is expected to corrode sooner. This paper shows that the ordering is reversed──the basest metal is protected by the thinnest film. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──standard electrode potentials, passivity and the Pilli...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

Halving the Size Beats Changing the Material Forty Times Over ── Spheres of radius 5 mm and 20 cm have cooling time constants of 348.8333 and 13953.3333 seconds, a ratio of exactly 40.000000000 ── changing the material from water to metal at one size gives only 1.3081 ── what sets the cooling is not specific heat but the surface-to-volume ratio ── [Paper 465]

How fast a thing cools is thought to be set by its material. This paper shows that size acts 40 times harder──changing from water to metal gives only 1.3081. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──Newton’s law of cooling, the lumped capacitance method and t...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

To Protect It, Something Must Dissolve First ── Attach zinc and the difference is +0.32 V and the iron is protected; attach copper and it is -0.78 V and the iron goes faster ── the protector loses 10.6920 kg per ampere-year ── the same act of attaching a metal reverses sign ── [Paper 440]

Protecting a metal is thought to mean covering it. This paper shows that there is a way of protecting that does not cover but attaches something that dissolves first──and that attaching the wrong metal reverses the sign. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claime...

Yuuki Yamagishi · 0 citations
#reinforcement learning Conference Open access Sep 2026

Progress and Analysis of Optimization for Large Language Models Based on Reinforcement Learning

The boundaries of how reinforcement learning optimizes the reasoning capabilities of large language models under different resource and scale constraints are reviewed, as well as the adaptability of reinforcement learning's optimization of large language models in different scenarios are analyzed.

Feng-Rui Tian · 0 citations
#small language model Open access Sep 2026

What Makes It Judder Is Not the Size of the Friction but the Gap Between Two ── With static 30 N, kinetic 20 N and a spring of 1000 N/m, each slip jumps 20.0000 mm ── make the two equal and the amplitude is exactly 0 ── stiffen the spring tenfold and it only falls to a tenth; it does not go ── [Paper 439]

Heavy friction is expected to make motion jerky. This paper shows that the cause is not the size but the gap──make the two frictions equal and the motion is smooth however large they are. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is claimed──the distinction between static...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

The NEMS Framework: No External Model Selection as a Principle of Foundational Self-Containment

This paper provides a high-level narrative summary of the physics arc (Papers 01–25) of the NEMS suite: semantic closure, self-containment, and their consequences in physics and quantum gravity. The suite introduces a formal "no external model selection" principle, classifies realized systems into a small set of univer...

Nova Spivack · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

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