#!/usr/bin/env python3

import sys
# import math
# import re                                    # re.compile(pattern) => ptn obj; p.search(s), p.match(s), p.finditer(s) => match obj; p.sub(after, s)
# from collections import deque                # deque class. deque(L): dq.append(x), dq.appendleft(x), dq.pop(), dq.popleft(), dq.rotate()
# from collections import defaultdict          # subclass of dict. defaultdict(facroty)
# from collections import Counter              # subclass of dict. Counter(iter): c.elements(), c.most_common(n), c.subtract(iter)
# from heapq import heapify, heappush, heappop # built-in list. heapify(L) changes list in-place to min-heap in O(n), heappush(heapL, x) and heappop(heapL) in O(lgn).
# from heapq import nlargest, nsmallest        # nlargest(n, iter[, key]) returns k-largest-list in O(n+klgn).
# from itertools import count, cycle, repeat   # count(start[,step]), cycle(iter), repeat(elm[,n])
# from itertools import groupby                # [(k, list(g)) for k, g in groupby('000112')] returns [('0',['0','0','0']), ('1',['1','1']), ('2',['2'])]
# from itertools import starmap                # starmap(pow, [[2,5], [3,2]]) returns [32, 9]
# from itertools import product                # product(iter, repeat=n)
# from itertools import accumulate             # accumulate(iter[, f])
# from functools import reduce                 # reduce(f, iter[, init])
# from functools import lru_cache              # @lrucache ...arguments of functions should be able to be keys of dict
# from bisect import bisect_left, bisect_right # bisect_left(a, x, lo=0, hi=len(a)) returns i such that all(val<x for val in a[lo:i]) and all(val>-=x for val in a[i:hi]).
# from copy import deepcopy                    # to copy multi-dimentional matrix without reference
# from fractions import gcd                    # for Python 3.4


def main():
    mod = 1000000007                  # 10^9+7
    inf = float('inf')
    sys.setrecursionlimit(10**6)    # 1000 -> 1000000
    def input(): return sys.stdin.readline().rstrip()
    def ii():  return int(input())
    def mi():  return map(int, input().split())
    def mi_0(): return map(lambda x: int(x)-1, input().split())
    def lmi(): return list(map(int, input().split()))
    def lmi_0(): return list(map(lambda x: int(x)-1, input().split()))
    def li():  return list(input())
    

    
    n, k = mi()
    L = [-float('inf')] + lmi()    # 1-index
    L.sort()

    FACT_MOD = [1] * (n + 1)    # i! % mod が FACT_MOD(i) に登録される
    for i in range(1, n+1):
        FACT_MOD[i] = (FACT_MOD[i-1] * i) % mod

    def combination(n, r, mod):
        """
        フェルマーの小定理 
        a ^ p-1 ≡ 1 (mod p)
        a ^ p-2 ≡ 1/a (mod p) (逆元)
        nCr = (n!) / ((n-r)! * r!) だが、mod p の世界ではこの分母を逆元を用いて計算しておくことが可能
        
        >>> m = 1000000007
        >>> combination(10, 5, m)
        252
        >>> combination(100, 50, m)
        538992043
        """
        numerator = FACT_MOD[n]
        denominator = (FACT_MOD[n-r] * FACT_MOD[r]) % mod
        # pow はすでに繰り返し二乗法で効率的に実装されている
        return (numerator * pow(denominator, mod-2, mod)) % mod
    # ==================================    

    ans = 0
    prev = 0
    # k up to n
    for i in range(k, n + 1):
        prev = (prev + combination(i-2, k-2, mod)) % mod
        # print(prev)
        ans = (ans + prev * L[i]) % mod
        # print(f"{i} {ans}")
    
    prev = 0
    # n-k+1 down to 1
    for j in range(n - k + 1, 0, -1):
        prev = (prev + combination(n-j-1, k-2, mod)) % mod
        ans = (ans - prev * L[j]) % mod
        # print(f"{j} {ans}")
    
    print(ans)



if __name__ == "__main__":
    main()

Measured memory_bytes: 14044