Amitava Das
Professor, BITS Goa | Former Research Associate Professor, AIISC, USA
Model Scale
12.4B
Dense Parameters
CoT Reliability
94.2%
Success on Complex Tasks
Avg Latency
42ms
Action Token Generation
Adaptability
High
Zero-Shot Capabilities
01. RAW INPUT DATA
Scenario: Dynamic Manipulation
Scenario: Locomotion Terrain
Scenario: Spatial Mapping
02. PROCESSED RESULTS
> vision_input: detected_object_sphere
> cot_init: plan_approach_vector
> reasoning: calculate_torque_limits
> action_tokens: [0.12, -0.44, 0.89, 0.0]
> feedback: contact_established
> cot_init: plan_approach_vector
> reasoning: calculate_torque_limits
> action_tokens: [0.12, -0.44, 0.89, 0.0]
> feedback: contact_established
Task: Precise Placement
Model decomposes high-level instructions into executable joint-space vectors with continuous feedback loops.
> state: walking_gait_unstable
> loc_aware: adjust_center_of_mass
> reasoning: shift_left_pedal_pressure
> action_tokens: [0.05, 0.22, -0.11, 0.9]
> status: balance_restored
> loc_aware: adjust_center_of_mass
> reasoning: shift_left_pedal_pressure
> action_tokens: [0.05, 0.22, -0.11, 0.9]
> status: balance_restored
Task: Terrain Recovery
Integration of IMU data into the transformer context window allows for immediate postural correction.
> user_input: "fetch the blue beaker"
> visual_search: active_scan
> cot: identify_beaker_depth_map
> reasoning: grasp_point_optimization
> action_tokens: [0.88, 0.12, -0.34, 0.5]
> visual_search: active_scan
> cot: identify_beaker_depth_map
> reasoning: grasp_point_optimization
> action_tokens: [0.88, 0.12, -0.34, 0.5]
Task: Zero-Shot Fetch
Natural language instruction to complex action mapping via internal semantic reasoning chain.
Analysis 01
94.2% Peak Efficiency
Performance remains logarithmic even as spatial complexity increases, demonstrating the robustness of LA-CoT reasoning.
Analysis 02
~42ms Optimized Path
PragyaVLA achieves a 2.4x latency reduction compared to existing vision-action architectures by offloading non-critical reasoning to background threads.
Contributors
Aman Chadha
GenAI Leadership @ AWS | Stanford AI | Ex-Amazon Alexa, Nvidia, Qualcomm | EB-1 "Einstein Visa" Recipient | EMNLP 2023 Outstanding Paper Award
Vasu Sharma
Applied Research Scientist Lead at Facebook AI Research | 6k+ citations | Ex-Citadel | CMU | IIT Kanpur | Startup Advisor & Mentor | Angel Investor | EB1A green card recipient
Vinija Jain
AI @ Meta | Ex-Amazon, Oracle, PANW | Stanford AI | EMNLP Outstanding Paper Award Recipient