12 citations · 14 across the 14 of their papers we have counts for
5 papers · 1 filter
The Perceptual Observatory Characterizing Robustness and Grounding in MLLMs
Tejas Anvekar, Fenil Bardoliya, Pavan K. Turaga +2
Recent advances in multimodal large language models (MLLMs) have yielded increasingly powerful models, yet their perceptual capacities remain poorly characterized. In practice, mos…
TabReX : Tabular Referenceless eXplainable Evaluation
Tejas Anvekar, Junha Park, Aparna Garimella +1
Evaluating the quality of tables generated by large language models (LLMs) remains an open challenge: existing metrics either flatten tables into text, ignoring structure, or rely…
Is Architectural Complexity Overrated? Competitive and Interpretable Knowledge Graph Completion with RelatE
Abhijit Chakraborty, Chahana Dahal, Ashutosh Balasubramaniam +2
We revisit the efficacy of simple, real-valued embedding models for knowledge graph completion and introduce RelatE, an interpretable and modular method that efficiently integrates…
TabXEval: Why this is a Bad Table? An eXhaustive Rubric for Table Evaluation
Vihang Pancholi, Jainit Bafna, Tejas Anvekar +2
Evaluating tables qualitatively and quantitatively poses a significant challenge, as standard metrics often overlook subtle structural and content-level discrepancies. To address t…
Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective
Krishna Singh Rajput, Tejas Anvekar, Chitta Baral +1
Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large language models. While these approache…