Mahsa Pahlavikhah Varnosfaderani

most citedUsing Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO

_{2}

, and other Environmental Factors

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2026

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents

Abhilasha Lodha, Mahsa Pahlavikhah Varnosfaderani, Abir Chakraborty +1

Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can cause context overflow, stale-…

cs.CL2022

emojiSpace: Spatial Representation of Emojis

Moeen Mostafavi, Mahsa Pahlavikhah Varnosfaderani, Fateme Nikseresht +1

In the absence of nonverbal cues during messaging communication, users express part of their emotions using emojis. Thus, having emojis in the vocabulary of text messaging language…

cs.LG2022★ 1 cited

Using Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO $_{2}$ , and other Environmental Factors

Mahsa Pahlavikhah Varnosfaderani, Arsalan Heydarian, Farrokh Jazizadeh

Dynamic models of occupancy patterns have shown to be effective in optimizing building-systems operations. Previous research has relied on CO $_{2}$ sensors and vision-based technique…

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents

emojiSpace: Spatial Representation of Emojis

Using Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO2​, and other Environmental Factors

Using Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO $_{2}$ , and other Environmental Factors