LLM-jp-4.1 Post-Training Dataset
Collection
4 items • Updated • 2
ID stringlengths 31 33 | messages stringlengths 451 17.6k | chosen_analysis stringlengths 11 11.7k | chosen_final stringlengths 1 13.1k | rejected_analysis stringlengths 13 14.4k | rejected_final stringlengths 1 14.3k |
|---|---|---|---|---|---|
daring_anteater_en-28265-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2029-06-10", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to provide code? Probably give example using Pygame. Provide minimal script. | **Python + Pygame – Minimal Platformer**
```python
# platformer.py
import pygame
from pygame.locals import *
# ---- Settings -------------------------------------------------
WINDOW_WIDTH = 800
WINDOW_HEIGHT = 600
FPS = 60
GRAVITY = 0.5 # pixels per frame²
JUMP_SPEED = -15 # initial upward velocity whe... | We need to provide code? Probably give example using Pygame. Provide concise script. | **Python + Pygame – Minimal Platformer**
```python
import pygame
import sys
# -------------------- Settings --------------------
WIDTH, HEIGHT = 800, 600
FPS = 60
GRAVITY = 0.5
JUMP_SPEED = -12
PLAYER_SPEED = 5
# -------------------- Helper classes --------------------
class Player(pygame.sprite.Sprite):
def __i... |
daring_anteater_en-50152-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-08-30", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need a blog post. Provide content. | **Agribusiness at the Crossroads: Challenges and Opportunities for Global Food Security**
*By [Your Name] – Date*
---
### Introduction
The world’s appetite is growing faster than ever. By 2050, the United Nations projects that we will need to feed roughly **9.7 billion people**, a 30‑percent increase from today. A... | We need a blog post. Provide content accordingly. | **Agribusiness — Balancing Challenges and Opportunities to Secure Global Food Supply**
*By [Your Name], Agri‑Tech Analyst | Date*
---
### Introduction
As world populations edge toward 10 billion by mid‑century, feeding everyone while preserving ecosystems has become the defining challenge of our era. Agribusiness ... |
daring_anteater_en-15654-turn1--1 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-04-07", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to provide code. Probably Python. Simple function. | ```python
def filter_by_length(strings, length):
"""
Return a new list containing only those strings whose length equals `length`.
Parameters
----------
strings : iterable of str
The collection of strings to examine.
length : int
Desired string length.
Returns
-------
... | We need to output code. Probably Python function. Provide minimal. | ```python
def filter_by_length(strings, target_len):
"""
Return a new list containing only those strings whose length equals `target_len`.
Parameters
----------
strings : iterable of str
The collection of strings to examine.
target_len : int
Desired string length.
Returns
... |
daring_anteater_en-87432-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2027-07-24", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to produce code plus brief tutorial <=500 words. Provide Python program with UI (CLI). Also explain combinatorics. Let's craft within limit. | **Coin‑Change Calculator – Python 3**
```python
#!/usr/bin/env python3
"""
Coin‑change calculator
----------------------
Given an amount N and a list of coin denominations C = [c1,…,ck] (positive integers),
the script prints the number of distinct ways to make exactly N units of money,
order of coins does NOT matter (... | We need to produce code plus brief tutorial <=500 words. Provide Python example with UI (CLI). Include explanation. | **Program – “Coin‑Change Counter”**
*Python 3, console based (no external libraries)*
```python
#!/usr/bin/env python3
"""
Coin‑Change Counter
------------------
Enter an amount (in cents) and a list of coin values (also in cents).
The program prints the number of distinct ways to make exact change.
How it works:... |
daring_anteater_en-89390-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2028-12-11", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to produce a screenplay. Provide scenes, dialogue, etc. Probably concise but detailed enough. | **Title:** *“Fossil Tides – The Story of Life’s Ocean”*
**Length:** ~6 minutes (≈12‑15 script pages)
**Target Audience:** Upper‑elementary / middle school students
---
### CHARACTER LIST
| Symbol | Role | Description |
|--------|------|-------------|
| **NARRATOR** | Voice‑over guide | Warm, enthusiastic, expla... | We need to produce a screenplay. Provide scenes, dialogue, narration. Probably concise but detailed enough. | **Title:** *“Fossil Tides – The Story of Life’s Deep Sea”*
**Format:** Animated short (≈7 minutes) – voice‑over + characters (Narrator, Fossil Fish, Ancient Turtle, Modern Shark, Kids).
---
### SCENE 1 – OPENING SHOT
**Visual:** A bright sunrise over a calm coastal bay; waves roll onto a sandy beach where a gro... |
daring_anteater_en-74679-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2026-07-23", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need produce ~500 words essay with citations. Provide references. | **The Italian and Northern Renaissances: Convergences and Divergences**
The Renaissance unfolded across Europe as a cultural rebirth characterized by renewed interest in classical antiquity, humanist scholarship, and innovative artistic techniques. While the Italian Renaissance emerged first—centered on city‑states su... | We need produce <=500 words paper with citations and references. Provide concise comparison. Use maybe APA style. | **The Italian and Northern Renaissances: Converging Ideals, Divergent Contexts**
The Renaissance emerged across Europe as a cultural rebirth grounded in renewed interest in antiquity, humanism, and empirical observation. While both the Italian and Northern Renaissances shared core intellectual currents—classical reviv... |
daring_anteater_en-63775-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2029-10-18", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to provide modified function handling signed two's complement, plus explanation of sign bit interpretation. Provide code and brief explanation. | **Modified function**
```python
def bin_to_signed_dec(binary_str: str) -> int:
"""
Convert a binary string (optionally prefixed with ``0b``) to a signed
decimal integer using two’s‑complement representation.
Parameters
----------
binary_str : str
Binary digits only; may start with ``0b... | We need to provide modified function handling signed two's complement, with explanation of sign bit interpretation. Follow instructions: give code and brief explanation. No extra fluff. | **Modified function**
```python
def bin_to_signed_dec(binary_str: str) -> int:
"""
Convert a binary string (two’s‑complement) to its signed decimal value.
Parameters
----------
binary_str : str
Binary digits optionally prefixed with ``0b``. Length defines the word size;
the most‑si... |
daring_anteater_en-81690-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-06-14", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need just formulation. Provide objective and constraints. | **Primal LP (maximization)**
Let
\(x_A\) = number of batteries A produced
\(x_B\) = number of batteries B produced
\[
\begin{aligned}
\text{Maximize } \; & Z = x_A + x_B \\[4pt]
\text{s.t. }
& 3x_A + 2x_B \;\le\; 120 \qquad\text{(labor‑hours constraint)}\\
& \frac{x_A}{5h} + \frac{x_B}{5h} \;\le\; 8 \quad\Lo... | We need formulate LP. Decision variables x_A, x_B. Maximize z = x_A + x_B subject to labor: 3x_A+2x_B ≤120; machines: (production rate?) Each machine can produce at most 5 batteries per hour, total capacity over time? Assuming same horizon as labor hours? Probably total production limited by machines * time: machines*h... | **Decision variables**
\(x_{A}\) = number of type‑A batteries to produce
\(x_{B}\) = number of type‑B batteries to produce
**Objective (maximise total output)**
\[
\text{Maximise } \; Z = x_{A}+x_{B}
\]
**Constraints**
1. **Labor availability** (total labour‑hours cannot exceed 120):
\[
3x_{A} + 2x_{... |
daring_anteater_en-98799-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2029-05-15", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | Need concise answer with details. | ### Interoperable Metadata & Rights‑Management in Practice
Below is a step‑by‑step illustration of a typical workflow – from creation to consumption – showing which standards are used at each stage, who inserts the data, and how downstream tools can read and act on it.
| Stage | Actor | Action | Standards / Technica... | Need concise answer with details. | ### Interoperable Metadata & Rights‑Management Tags – A Concrete Implementation Blueprint
| Step | Who acts | Standard(s) used | Technical actions | Example payload |
|------|----------|------------------|-------------------|-----------------|
| **1️⃣ Define the rights schema** | Rights‑holder consortium (e.g., WIPO... |
daring_anteater_en-63662-turn1--1 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-12-04", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We compute product = (9.2*10^2)*(8*10^6)=9.2*8 *10^{8}=73.6*10^8=7.36*10^9 (standard scientific notation). That's 7.36 ×10^9. Standard form means one digit before decimal, so that's it. Number of zeros after decimal? Actually ask "how many zeroes are in the product" likely number of zero digits in the integer part when... | 7 | We need compute product then write in standard form (scientific notation) and count zeros after decimal before coefficient? Standard form means like a ×10^b with one non-zero digit before decimal. So multiply: 9.2*10^2 = 920; actually 9.2×10^2=9.2*100=920. Then times 8×10^6 = 8,000,000. Multiply: 920 * 8,000,000 = 920*... | 8 |
daring_anteater_en-98632-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-02-09", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | Need to give key metrics and case study template. Chinese response. | ## 一、衡量福利／工具投入产出比（ROI）的关键指标
| 大类别 | 指标名称 | 含义与计算方式 | 数据来源 | 为什么重要 |
|--------|----------|----------------|----------|-------------|
| **财务层面** | 成本节约额 | （离职成本下降额 + 病假天数减少导致的生产力提升）‑ 项目直接费用 | HR系统、工资单、病假记录、项目预算 | 直接体现经济回报 |
| | 投资回报率（ROI） | \[(净收益 ÷ 总投入) × 100%\]<br>净收益 = 财务节约额 + 间接价值（如品牌提升） | 同上 | 衡量整体效益大小 |... | Need provide KPI list and case template. Chinese answer. | ## 一、衡量福利／工具投入产出比（ROI）的核心指标
| 大类别 | 关键 KPI | 计算方式 / 数据来源 | 为什么重要 |
|--------|----------|-------------------|------------|
| **财务层面** | ① 成本节约额（Turnover Cost Savings）<br>② 投资回报率（ROI %） | 节约 = （离职率下降 × 平均招聘成本）+（生产力提升 × 人均利润贡献）<br>ROI% = (节约额 − 投入费用) ÷ 投入费用 × 100% | 直接显示公司钱包得到多少回报。 |
| **人力资本** | ③ 员工保留率（Retention Rate... |
daring_anteater_en-99479-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2029-03-04", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need answer likely which option matches clue? "Our only satellite is found with the other:" maybe asking which of these groups includes our only satellite (moon) together with something else. Moon is Earth's only natural satellite; it's found with the other... The phrase ambiguous. Could be that the moon belongs to ... | A | We need to pick which option fits clue? "Our only satellite is found with the other:" maybe means Earth's only natural satellite (Moon) is found with... The Moon is part of solar system containing the moon. So answer likely A: nine planets includes moon. But phrasing weird. Probably ask which list contains our only sat... | A |
daring_anteater_en-40319-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2030-05-17", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to give size (number of ordered pairs). That's 8 as listed. Then provide grid/table visualization. Just answer. | **Size of C:** |C| = **8**
**Grid / Table view**
```
b=3 b=4 b=5
+------+-------+------+
a=1 | (1,3) | (1,4) | (1,5) |
+------+-------+------+
a=2 | (2,3) | (2,4) | (2,5) |
+------+-------+------+
a=3 | | (3,4) | (3,5) |
+------+-------+------+
``` | We need to give size and visualization grid/table. Provide concise answer. | **Size of \(C\)**
The set \(C\) contains 8 ordered pairs, so \(|C| = 8\).
**Grid / Table representation**
```
b=3 b=4 b=5
+-------------------
a=1 | (1,3) | (1,4) | (1,5) |
a=2 | (2,3) | (2,4) | (2,5) |
a=3 | (3,4) | (3,5) | — |
```
Only the cells where the entry in row \(a\) is less than the c... |
daring_anteater_en-59688-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2027-03-17", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to explain solution. Provide reasoning. | **Step 1 – Understand the condition**
The equation
\[
z^{5}+2004z=1 \qquad (1)
\]
defines five (complex) roots; call them \(z_{1},z_{2},z_{3},z_{4},z_{5}\).
For each root we have
\[
z_i^{5}=1-2004z_i .
\]
Squaring both sides gives
\[
z_i^{10}=(1-2004z_i)^2 .
\]
Expanding,
\[
z_i^{10}=1-4008z_i+2004^{2}z... | We need to explain derivation. Provide reasoning. | **Step 1 – The roots of the given equation**
The condition
\[
z^{5}+2004z=1
\qquad\Longleftrightarrow\qquad
z^{5}+2004z-1=0
\]
defines a quintic whose five (complex) zeros we call \(r_{1},r_{2},r_{3},r_{4},r_{5}\).
Because it is monic, Vieta’s formulas give
\[
\begin{aligned}
\sigma_1 &= r_{1}+r_{2}+r_{3}+r_{4... |
daring_anteater_en-21251-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2026-03-02", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | Need concise explanation linking duality to QM formalism, operators, commutators, Heisenberg uncertainty, plus concrete example e.g., position-momentum of electron double-slit. Provide succinct but complete. | ### From wave‑particle duality to the quantum‐mechanical formalism
| Step | Physical idea (duality) | Formal translation in QM | Consequence |
|------|--------------------------|---------------------------|-------------|
| 1️⃣ | **Wave description** – a free particle is represented by a sinusoidal plane wave \(\psi... | We need concise explanation, include formal incorporation, operators, commutators, Heisenberg principle, plus concrete example e.g., position-momentum. Provide equations. No extra fluff. | ### Formal role of wave‑particle duality in quantum mechanics
| Step | Physical idea | Mathematical implementation |
|------|--------------|-----------------------------|
| **1. State description** | A physical system is described by a *wave* (a complex‐valued function) rather than a classical trajectory. | The stat... |
daring_anteater_en-24071-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2028-01-22", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need an essay ≤250 words. Provide content as requested. | During my first year living alone in a small apartment, I decided to make sustainability a daily habit rather than a weekend project. The most immediate change was switching to reusable containers for food storage and meal prep instead of disposable plastic bags. My kitchen cabinets were already cramped, so finding spa... | We need an essay <=250 words. Provide content as requested. | During my first year living alone in a downtown apartment, I decided to make sustainability a daily habit rather than a weekend project. The most immediate change was switching from single‑use plastic water bottles to a reusable stainless‑steel bottle. My kitchen’s small fridge lacked space for bulk containers, so I of... |
daring_anteater_en-96902-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2028-07-26", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | Provide list of five with descriptions. | **1. Joseph Engelberger (1925‑2015)**
*Founder of modern industrial robotics.* Co‑inventor of the first commercially successful robot, the Unimate (1961), which automated welding on automobile assembly lines. His work established the business case for robotic automation, leading to today’s widespread use of collabora... | Provide list 5 with descriptions. | 1. **Rodney Brooks** – Co‑founder of iRobot and former MIT professor; pioneered behavior‑based (subsumption) architecture and swarm robotics, demonstrating that complex robot behaviors can emerge from simple local rules without centralized control.
2. **Hiroshi Ishiguro** – Director of Osaka University’s Intelligent S... |
daring_anteater_en-65943-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2027-05-12", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need first four terms sum. Common difference d = (9-5)=4. So terms: t5=5 => t1 = t5 -4d*? Actually t_n = a + (n-1)d. Let a = first term. Then t5 = a+4d =5, t6 = a+5d=9, check gives d=4 indeed because subtract gives 1d=4 so consistent. Solve a+4*4=5 → a+16=5 → a=-11. First four terms: -11, -7, -3, 1. Sum = (-11-7-3+1... | \[
a_1 = -11,\qquad a_2 = -7,\qquad a_3 = -3,\qquad a_4 = 1
\]
\[
S_{1-4}=a_1+a_2+a_3+a_4=(-11)+(-7)+(-3)+(1)=-20
\]
**Answer:** \(-20\). | We need find common difference d = 4 (since consecutive terms increase by 4). Given term5=5, term6=9 => d=4. So term1 = term5 -4*d =5-20= -15. Terms: t1=-15,t2=-11,t3=-7,t4=-3. Sum first four = -36. | \[
d = 9-5 = 4,\qquad
a_1 = a_5 -4d = 5 - 4\cdot4 = -15.
\]
Thus
\(a_1 = -15,\; a_2 = -11,\; a_3 = -7,\; a_4 = -3\).
\[
S_{1-4}= -15-11-7-3 = -36.
\]
**Answer:** \(-36\). |
daring_anteater_en-21214-turn2--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2027-09-05", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to give step-by-step derivation and discuss assumptions. Provide concise but detailed explanation. | ### Pas a pas – deducció de la condició d’optimalitat
Considerem un problema de control lineal‑quadratic dins de la formulació HJB
\[
J[u]=\int_{0}^{T}L\!\bigl(x(t),u(t)\bigr)\,dt+\Phi\bigl(x(T)\bigr),
\qquad
\dot x = f\!\bigl(x,u\bigr),
\]
on s’utilitza una funció de valor continua \(V(x)\) que satisfaixi l’EG... | We need to give step-by-step derivation and assumptions. No extra fluff. | ### Derivament pas a pas de \(\displaystyle \frac{\partial}{\partial u}[L+V_x f]=0\)
Suposem que tenim
\[
L=L(x,u),\qquad f=f(x,u),\qquad V_x:=\frac{\partial V}{\partial x}.
\]
El Hamiltoniane d’un problema continuo‐tempo és
\[
H(x,u,V_x)=L(x,u)+V_x\,f(x,u).
\]
Per a una minimització convexa en el control s’ut... |
daring_anteater_en-78194-turn1--0 | [{"role": "system", "name": null, "content": [{"model_identity": "You are LLM-jp-4, a large language model trained by LLM-jp.", "reasoning_effort": "Low", "conversation_start_date": "2027-03-05", "knowledge_cutoff": "2025-12", "channel_config": {"valid_channels": ["analysis", "commentary", "final"], "channel_required":... | We need to provide code using NLTK for sentiment analysis. Provide concise program. | ```python
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
# 初回だけ実行すれば OK（必要リソースのダウンロード）
nltk.download('vader_lexicon')
def analyze_sentiment(text: str) -> dict:
"""
与えられたテキストの感情スコアを返す。
Returns
-------
dict
{
"neg": float, # ネガティブ度合い (0‑1)
"neu":... | We need code example. Provide Python using NLTK's VADER. | ```python
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
# 初回実行時だけ必要（ダウンロードが済んでいなければ）
nltk.download('vader_lexicon')
def analyze_sentiment(text: str) -> dict:
"""
与えられたテキストの感情スコアを返す。
戻り値は VADER が提供する 4 種類のスコアを含む辞書:
{
"neg": ネガティブ度合い (0〜1),
"neu": ニュートラ度... |
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llm-jp-4.1-8b-thinking-dpo-data
Overview
This dataset is a Direct Preference Optimization (DPO) dataset used to train llm-jp-4.1-8b-thinking.
It is constructed by pairing multiple candidate responses for a given prompt and selecting preferred (chosen) and non-preferred (rejected) responses. The splits reasoning_low, reasoning_medium, and reasoning_high correspond to different reasoning effort settings used during response generation.
The fields chosen_analysis, chosen_final, rejected_analysis, and rejected_final are generated using a model trained via supervised fine-tuning (SFT). These responses are then evaluated by gpt-oss-120b, which determines the preferred (chosen) and non-preferred (rejected) responses.
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Data Sources and Licenses
The prompts used to construct this DPO dataset are derived from the following data sources. Since each source dataset has its own license, please ensure compliance with the respective licenses when using this dataset. Some subsets cannot be redistributed due to licensing restrictions and are therefore not included.
| Dataset | License | Notes |
|---|---|---|
| ac_self_inst | answer-carefully-dataset-tou | Not included due to redistribution restrictions |
| daring_anteater | CC BY 4.0 | - |
| flan | ODC-BY | - |
| ichikara | - | Requires paid license, not included |
| jaster_v1.4.1 | CC BY-SA 4.0, CC BY-SA 3.0, CC BY 4.0, BSD-3, Apache-2.0, MIT | - |
| llmjp_extraction_wiki_ja_v0.x | Apache-2.0 | - |
| llmjp_magpie_sft_v1.0 | Apache-2.0 | - |
| llmc_math_dataset | - | To be released |
| logical_math_coding_wizard8x22b | Apache-2.0 | - |
| multiturn_calm3 | Apache-2.0, CC BY-SA 3.0, CC0, CC BY 4.0 | - |
| nemotron_post_v2_stem | CC BY 4.0 | - |
| nemotron_post_v3_chat | CC BY 4.0 | - |
| nemotron_post_v3_if | CC BY 4.0 | - |
| nemotron_post_v3_math | CC BY-SA 4.0 | - |
| random_to_fixed_multiturn_calm3 | Apache-2.0 | - |
| synthetic_if_ja | - | To be released |
| synthetic_jp_en_coding | Apache-2.0 | - |
| nemotron3_sft_chat_v3 | CC BY 4.0, ODC-BY | - |
| nemotron3_sft_if_v3 | CC BY 4.0, ODC-BY | - |
| nemotron3_sft_science_vendor | CC BY-SA 4.0 | - |
| table_gpt_train_large | MIT | - |
| nemotron3_sft_multilingual_v2_math_ko_stackoverflow | CC BY-SA 4.0 | - |
| nemotron3_sft_multilingual_v2_math_ja_stackoverflow | CC BY-SA 4.0 | - |
Data Format
Each sample has the following format:
{
"ID": "...",
"messages": [
{"role": "system", "name": null, "content": ["..."]},
{"role": "user", "name": null, "content": ["..."]},
],
"chosen_analysis": "...",
"chosen_final": "...",
"rejected_analysis": "...",
"rejected_final": "..."
}
chosen_analysisrepresents the reasoning process (chain-of-thought) of the preferred responsechosen_finalrepresents the final response of the preferred responserejected_analysisrepresents the reasoning process of the non-preferred responserejected_finalrepresents the final response of the non-preferred response
The messages field contains the input conversation (prompt context).
This structure allows training preference models that compare two candidate responses conditioned on the same prompt.
Notes
- This dataset contains responses generated by a large language model.
- The preference labels (chosen vs rejected) are constructed automatically and may contain noise.
- Generated content may include errors, inaccuracies, biases, or harmful outputs.
Send Questions to
llm-jp(at)nii.ac.jp
Model Card Authors
The names are listed in alphabetical order.
Hirokazu Kiyomaru and Takashi Kodama.
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