Robots are usually unsuitable for altering different tasks and environments. General-purpose models of robots are devised to circumvent this problem. They allow fine-tuning these general-purpose models for a wide scope of robotic tasks. However, it is challenging to maintain the consistency of shared open resources across various platforms. Success in real-world environments is far from…
There is no gainsaying that artificial intelligence has developed tremendously in various fields. However, the accurate evaluation of its progress would be incomplete without considering the generalizability and adaptability of AI models for specific domains. Domain Adaptation (DA) and Domain Generalization (DG) have garnered ample attention from researchers across the globe. Given that training is…
Edge devices like smartphones, IoT gadgets, and embedded systems process data locally, improving privacy, reducing latency, and enhancing responsiveness, and AI is getting integrated into these devices rapidly. But, deploying large language models (LLMs) on these devices is difficult and complex due to their high computational and memory demands. LLMs are massive in size and…
Language models (LMs) have significantly progressed through increased computational power during training, primarily through large-scale self-supervised pretraining. While this approach has yielded powerful models, a new paradigm called test-time scaling has emerged, focusing on improving performance by increasing computation at inference time. OpenAI’s o1 model has validated this approach, showing enhanced reasoning capabilities through test-time…
Ad hoc networks are decentralized, self-configuring networks where nodes communicate without fixed infrastructure. They are commonly used in military, disaster recovery, and IoT applications. Each node acts as both a host and a router, dynamically forwarding data. Flooding attacks in ad hoc networks occur when a malicious node excessively transmits fake route requests or data…
Large Language Models (LLMs) are primarily designed for text-based tasks, limiting their ability to interpret and generate multimodal content such as images, videos, and audio. Conventionally, multimodal operations are task-specific models trained on large amounts of labeled data, which makes them resource-hungry and rigid. Zero-shot methods are also restricted to pretraining with paired multimodal datasets,…
OpenAI’s Deep Research AI Agent offers a powerful research assistant at a premium price of $200 per month. However, the open-source community has stepped up to provide cost-effective and customizable alternatives. Here are four fully open-source AI research agents that can rival OpenAI’s offering: 1. Deep-Research Overview:Deep-Research is an iterative research agent that autonomously generates…
Large Language Models (LLMs) have demonstrated notable reasoning capabilities in mathematical problem-solving, logical inference, and programming. However, their effectiveness is often contingent on two approaches: supervised fine-tuning (SFT) with human-annotated reasoning chains and inference-time search strategies guided by external verifiers. While supervised fine-tuning offers structured reasoning, it requires significant annotation effort and is constrained by…
Reinforcement Learning RL trains agents to maximize rewards by interacting with an environment. Online RL alternates between taking actions, collecting observations and rewards, and updating policies using this experience. Model-free RL (MFRL) maps observations to actions but requires extensive data collection. Model-based RL (MBRL) mitigates this by learning a world model (WM) for planning in…
Despite recent advancements, generative video models still struggle to represent motion realistically. Many existing models focus primarily on pixel-level reconstruction, often leading to inconsistencies in motion coherence. These shortcomings manifest as unrealistic physics, missing frames, or distortions in complex motion sequences. For example, models may struggle with depicting rotational movements or dynamic actions like gymnastics…