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Language Models
+have+garnered+widespread+attention+due+to+their+remarkable+performance+across+various+tasks.+However%252C+to+mitigate+the+issue+of+hallucinations%252C+LLMs+often+incorporate+retrieval-augmented+pipeline+to+provide+them+with+rich+external+knowledge+and+context.+Nevertheless%252C+challenges+stem+from+inaccurate+and+coarse-grained+context+retrieved+from+the+retriever.+Supplying+irrelevant+context+to+the+LLMs+can+result+in+poorer+responses%252C+increased+inference+latency%252C+and+higher+costs.+This+paper+introduces+a+method+called+Instruction-Aware+Contextual+Compression%252C+which+filters+out+less+informative+content%252C+thereby+accelerating+and+enhancing+the+use+of+LLMs.+The+experimental+results+demonstrate+that+Instruction-Aware+Contextual+Compression+notably+reduces+memory+consumption+and+minimizes+generation+latency+while+maintaining+performance+levels+comparable+to+those+achieved+with+the+use+of+the+full+context.+Specifically%252C+we+achieved+a+50%2525+reduction+in+context-related+costs%252C+resulting+in+a+5%2525+reduction+in+inference+memory+usage+and+a+2.2-fold+increase+in+inference+speed%252C+with+only+a+minor+drop+of+0.047+in+Rouge-1.+These+findings+suggest+that+our+method+strikes+an+effective+balance+between+efficiency+and+performance.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.2811274576a8201af6bdd2019c0ca368%3frik%3d%252beef8ebMl0Phvg%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Contextual+Language+Models&FORM=IRPRST&ck=C35397E1CAC8BE7F51376E45EDA8B9A2&selectedIndex=18&itb=0)
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