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rl-introduction
Commit 80e68ccc by 周航
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Update the figure of section4

parent 9bf1efa9
正在显示 包含 68 行增加 和 181 行删除
section4/Figures/figure-rm-evaluation.tex
\begin{tikzpicture}[
box/.style={
draw,
rectangle,
minimum height=0.85cm,
minimum width=1.65cm,
align=center,
font=\small,
thick
},
smallbox/.style={
draw,
rectangle,
minimum height=0.6cm,
minimum width=1.2cm,
align=center,
font=\scriptsize,
thick
},
resultbox/.style={
box,
fill=rmgreen,
text width=2.9cm,
minimum width=3.15cm,
font=\scriptsize
},
arrow/.style={
-{Stealth},
thick
},
arrowlabel/.style={
midway,
above,
fill=white,
inner sep=1pt,
font=\scriptsize
},
subtitle/.style={
font=\bfseries\small
}
]
% colors
\definecolor{rmblue}{RGB}{190,210,240}
\definecolor{rmpink}{RGB}{245,190,200}
\definecolor{rmyellow}{RGB}{250,235,180}
\definecolor{rmgreen}{RGB}{190,230,190}
\definecolor{rmpurple}{RGB}{220,200,240}
\begin{center}
\begin{tikzpicture}[
box/.style={draw, rounded corners, rectangle, minimum height=0.85cm, minimum width=1.65cm, align=center, font=\scriptsize, anchor=west},
smallbox/.style={minimum height=0.6cm, minimum width=1.2cm, align=center, font=\scriptsize, anchor=west,},
resultbox/.style={box, fill=rmgreen, text width=2.9cm, minimum width=3.15cm, font=\scriptsize},
arrow/.style={->,},
arrowlabel/.style={midway, above, fill=white, inner sep=1pt, font=\scriptsize},
subtitle/.style={font=\bfseries\small}
]
\definecolor{rmblue}{RGB}{190,210,240}
\definecolor{rmpink}{RGB}{245,190,200}
\definecolor{rmyellow}{RGB}{250,235,180}
\definecolor{rmgreen}{RGB}{190,230,190}
\definecolor{rmpurple}{RGB}{220,200,240}
% ======================
% (a) RL-based Evaluation
% ======================
\scriptsize
\node[box, fill=rmpurple] (rm)
at (-5.25,4.35) {Reward\\Model};
\begin{scope}[local bounding box=pa]
\node[box, fill=rmblue] (rl)
at (-1.75,4.35) {RL\\Training};
\node[text width=8cm] (patitle) at (0,0)
{blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla blabla};
\node[box, fill=rmpurple!60,anchor=north west] (rma) at ([yshift=-0.1cm]patitle.south west) {Reward \\ Model A};
\node[box, fill=rmpurple!60,anchor=north] (rmb) at ([yshift=-0.2cm]rma.south) {Reward \\ Model B};
\node[box, fill=rmyellow]
(policy)
at (1.75,4.35) {Policy\\LLM};
\node[box, fill=rmblue!60] (rl) at ([xshift=2cm]$1/2*(rma.east)+1/2*(rmb.east)$) {RL\\Training};
\node[box, fill=rmyellow!60] (policy) at ([xshift=3cm]rl) {Policy\\LLM};
\node[box, fill=rmgreen]
(bench)
at (5.25,4.35) {Benchmark};
\node[box, fill=rmgreen!60,anchor=north west] (bencha) at ([xshift=2cm]rma.north-|policy.east) {Score of \\ Reward Model A};
\node[box, fill=rmgreen!60,anchor=north west] (benchb) at ([xshift=2cm]rmb.north-|policy.east) {Score of \\ Reward Model B};
\node[anchor=south] at ([yshift=0.1cm]bencha.north) {\textbf{Evaluation Results}};
\path[draw,dashed,rounded corners] ([xshift=1.75cm]rma.north east) rectangle ([xshift=-1.75cm]benchb.south west);
\draw[arrow] (rm)--(rl)
node[arrowlabel]{reward signal};
\draw[arrow] (rma.east) -- node[below,align=center]{reward signal} +(1.75cm,0);
\draw[arrow] (rmb.east) -- +(1.75cm,0);
\draw[arrow] (rl)--(policy) node[arrowlabel]{RL training};
\draw[arrow] ([xshift=-1.75cm]bencha.west) -- node[below,align=center]{benchmark} +(1.75cm,0);
\draw[arrow] ([xshift=-1.75cm]benchb.west) -- +(1.75cm,0);
\draw[arrow] (rl)--(policy)
node[arrowlabel]{RL training};
\node[subtitle,anchor=north] at ([yshift=-0.1cm]$1/2*(rmb.south west)+1/2*(benchb.south east)$) {(a) RL-based Evaluation};
\draw[arrow] (policy)--(bench)
node[arrowlabel]{benchmark};
\end{scope}
\begin{scope}[shift={({$(pa)-(8,0)$}|-(0,-5.5))},local bounding box=pb]
\node[smallbox] (pair-input) at (0,0) {$(x,y^+,y^-)$};
\node[subtitle] at (0,3.55) {(a) RL-based Evaluation};
\node[box,fill=rmblue!60] (rma) at ([xshift=1.5cm,yshift=.75cm]pair-input.east) {Reward\\Model A};
\node[box,fill=rmpink!60] (rmb) at ([xshift=1.5cm,yshift=-.75cm]pair-input.east) {Reward\\Model B};
\node[smallbox] (a-result) at ([xshift=1.5cm]rma.east) {$y^+>y^-$};
\node[smallbox] (b-result) at ([xshift=1.5cm]rmb.east) {$y^+<y^-$};
\node[anchor=south,align=center] at ([yshift=0.1cm]a-result.north) {\textbf{Evaluation}\\\textbf{Results}};
\node[text width=5cm,anchor=south west] (pair-eval) at ([yshift=0.1cm]pair-input.west|-rma.north)
{Evaluation Result Human prefers $y^+$ Model A correct};
% ======================
% (b) Pairwise
% ======================
\draw[arrow] (pair-input)--(rma);
\draw[arrow] (pair-input)--(rmb);
\draw[arrow] (rma)--(a-result);
\draw[arrow] (rmb)--(b-result);
\node[smallbox] (pair-input)
at (-6.85,-0.45)
{$(x,y^+,y^-)$};
\node[subtitle,anchor=north,yshift=-0.25cm] (subb) at ({$1/2*(pair-input.west)+1/2*(b-result.east)$}|-rmb.south)
{(b) Pairwise Ranking Evaluation};
\end{scope}
\node[box,fill=rmblue]
(rma)
at (-5.05,0.25)
{Reward\\Model A};
\begin{scope}[shift={({$2*(pa)-(pb.east)$}|-(0,-5.5))}]
\node[box,fill=rmpink]
(rmb)
at (-5.05,-1.1)
{Reward\\Model B};
\node[smallbox] (candidate) at (0,0) {$(x, y_1, y_2, y_3, \cdots)$};
\node[smallbox]
(a-result)
at (-3.3,0.25)
{$y^+>y^-$};
\node[box,fill=rmblue!60] (lrma) at ([xshift=1cm,yshift=.75cm]candidate.east) {Reward\\Model A};
\node[box,fill=rmpink!60] (lrmb) at ([xshift=1cm,yshift=-.75cm]candidate.east) {Reward\\Model B};
\node[smallbox]
(b-result)
at (-3.3,-1.1)
{$y^+<y^-$};
\node[smallbox] (best-a) at ([xshift=1cm]lrma.east) {Best is $y_3$};
\node[smallbox] (best-b) at ([xshift=1cm]lrmb.east) {Best is $y_4$};
\node[anchor=south,align=center] at ([yshift=0.1cm]best-a.north) {\textbf{Evaluation}\\\textbf{Results}};
\node[resultbox]
(pair-eval)
at (-4.05,1.45)
{Evaluation\\Result\\
Human prefers $y^+$\\
Model A correct};
\node[text width=5cm,anchor=south west] (list-eval) at ([yshift=0.1cm]candidate.west|-lrma.north)
{Evaluation Result Human selects $y_3$ RM-A better};
\draw[arrow] (candidate)--(lrma);
\draw[arrow] (candidate)--(lrmb);
\draw[arrow]
(pair-input)--(rma);
\draw[arrow] (lrma)--(best-a);
\draw[arrow] (lrmb)--(best-b);
\draw[arrow]
(pair-input)--(rmb);
\node[subtitle,anchor=north] at ({$1/2*(candidate.west)+1/2*(best-b.east)$}|-subb.north)
{(c) Listwise Ranking Evaluation};
\draw[arrow]
(rma)--(a-result);
\end{scope}
\draw[arrow]
(rmb)--(b-result);
\draw[arrow]
(a-result.north)--(pair-eval.south east);
\draw[arrow]
(b-result.north)--(pair-eval.south);
\node[subtitle] at (-4.05,-1.85)
{(b) Pairwise Ranking Evaluation};
% ======================
% (c) Listwise
% ======================
\node[smallbox]
(candidate)
at (1.15,-0.45)
{$y_1$\\$y_2$\\$y_3$\\$\cdots$};
\node[box,fill=rmblue]
(lrma)
at (3.0,0.25)
{Reward\\Model A};
\node[box,fill=rmpink]
(lrmb)
at (3.0,-1.1)
{Reward\\Model B};
\node[smallbox]
(best-a)
at (4.7,0.25)
{Best is\\$y_3$};
\node[smallbox]
(best-b)
at (4.7,-1.1)
{Best is\\$y_4$};
\node[resultbox]
(list-eval)
at (4.0,1.45)
{Evaluation\\Result\\
Human selects $y_3$\\
RM-A better};
\draw[arrow]
(candidate)--(lrma);
\draw[arrow]
(candidate)--(lrmb);
\draw[arrow]
(lrma)--(best-a);
\draw[arrow]
(lrmb)--(best-b);
\draw[arrow]
(best-a.north)--(list-eval.south east);
\draw[arrow]
(best-b.north)--(list-eval.south);
\node[subtitle] at (4.0,-1.85)
{(c) Listwise Ranking Evaluation};
\end{tikzpicture}
\end{tikzpicture}
\end{center}
section4/section4.tex
......@@ -220,8 +220,7 @@ After training a reward model, an important question is \textit{how to evaluate
\begin{figure*}[!t]
\centering
\resizebox{\linewidth}{!}{
\input{section4/Figures/figure-rm-evaluation.tex}}
\input{section4/Figures/figure-rm-evaluation.tex}
\caption{
Commonly used reward model evaluation approaches.
For the RL-based evaluation approach, the reward model is used to provide reward signals for policy optimization, and its quality is measured by the downstream performance of the optimized policy.
......
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