1 citations · 1 across the 8 of their papers we have counts for
11 papers
WaveCommitments: Private and Verifiable Speech-Agent Marketplaces
Oguzhan Baser, Kaan Kale, Sriram Vishwanath +1
Modern speech systems are evolving into ecosystems of autonomous speech agents that interact, negotiate, and trade assets such as embeddings, spectrograms, or raw data. In such mar…
ModalFidelity: Routing Modalities for Deepfake Detection on a Budget
Oguzhan Baser, Kaan Kale, Sriram Vishwanath +1
Deepfakes no longer need to fake a whole video. Generators that read the transcript now alter only the few seconds in which a video's meaning turns, so a forgery hides in a small,…
The Key Handoff: Retrieval in Hybrid Language Models
Kaan Kale, Oguzhan Baser, Sriram Vishwanath
A two-hop question makes a language model retrieve twice: once to produce a bridge entity, and once to retrieve with it. Transformers resolve that entity in their early layers. Hyb…
RoboShape: Information-Theoretic Point Cloud Representations for Privacy-Aware Robot Perception
Oguzhan Baser, Mirac Sozen, Kaan Kale +2
With the increased adoption of robotic agents operating in human environments by scanning and sharing 3D representations (e.g., for fleet learning, cloud-based planning, or collabo…
TensorCommitments: A Lightweight Verifiable Inference for Large Language Models
Oguzhan Baser, Elahe Sadeghi, Eric Wang +6
Most large language models (LLMs) run on external clouds: users send a prompt, pay for inference, and must trust that the remote GPU executes the LLM without any adversarial tamper…
AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs
Hakan Emre Gedik, Andrew Martin, Mustafa Munir +4
Vision Graph Neural Networks (ViGs) have demonstrated promising performance in image recognition tasks against Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs).…
Fair Resource Allocation for Fleet Intelligence
Oguzhan Baser, Kaan Kale, Po-han Li +1
Resource allocation is crucial for the performance optimization of cloud-assisted multi-agent intelligence. Traditional methods often overlook agents' diverse computational capabil…
WavShape: Information-Theoretic Speech Representation Learning for Fair and Privacy-Aware Audio Processing
Oguzhan Baser, Ahmet Ege Tanriverdi, Kaan Kale +2
Speech embeddings often retain sensitive attributes such as speaker identity, accent, or demographic information, posing risks in biased model training and privacy leakage. We prop…
PhonemeFake: Redefining Deepfake Realism with Language-Driven Segmental Manipulation and Adaptive Bilevel Detection
Oguzhan Baser, Ahmet Ege Tanriverdi, Sriram Vishwanath +1
Deepfake (DF) attacks pose a growing threat as generative models become increasingly advanced. However, our study reveals that existing DF datasets fail to deceive human perception…
SecureSpectra: Safeguarding Digital Identity from Deep Fake Threats via Intelligent Signatures
Oguzhan Baser, Kaan Kale, Sandeep P. Chinchali
Advancements in DeepFake (DF) audio models pose a significant threat to voice authentication systems, leading to unauthorized access and the spread of misinformation. We introduce…
TexShape: Information Theoretic Sentence Embedding for Language Models
Kaan Kale, Homa Esfahanizadeh, Noel Elias +3
With the exponential growth in data volume and the emergence of data-intensive applications, particularly in the field of machine learning, concerns related to resource utilization…