activity
20242026
most citedEnhancing Cross-Modal Contextual Congruence for Crowdfunding Success using Knowledge-infused Learning

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents

Trilok Padhi, Ramneet Kaur, Krishiv Agarwal +9

Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments. Despite their growing capabi…

cs.AI2025

Co-Evolving Agents: Learning from Failures as Hard Negatives

Yeonsung Jung, Trilok Padhi, Sina Shaham +4

Self-evolving agents improve their performance on long-horizon tasks by learning from their own interactions with an environment. A common approach uses the resulting failed trajec…

cs.AI2025★ 1 cited

Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks

Trilok Padhi, Pinxian Lu, Abdulkadir Erol +5

Large Language Model (LLM) agents are powering a growing share of interactive web applications, yet remain vulnerable to misuse and harm. Prior jailbreak research has largely focus…

cs.HC2025★ 1 cited

From Reddit to Generative AI: Evaluating Large Language Models for Anxiety Support Fine-tuned on Social Media Data

Ugur Kursuncu, Trilok Padhi, Gaurav Sinha +3

The growing demand for accessible mental health support, compounded by workforce shortages and logistical barriers, has led to increased interest in utilizing Large Language Models…

cs.CL2025

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding

Trilok Padhi, Ramneet Kaur, Adam D. Cobb +7

We introduce a novel approach for calibrating uncertainty quantification (UQ) tailored for multi-modal large language models (LLMs). Existing state-of-the-art UQ methods rely on co…

cs.CR2025★ 1 cited

Playing Devil's Advocate: Unmasking Toxicity and Vulnerabilities in Large Vision-Language Models

Abdulkadir Erol, Trilok Padhi, Agnik Saha +2

The rapid advancement of Large Vision-Language Models (LVLMs) has enhanced capabilities offering potential applications from content creation to productivity enhancement. Despite t…

cs.LG2024

Just KIDDIN: Knowledge Infusion and Distillation for Detection of INdecent Memes

Rahul Garg, Trilok Padhi, Hemang Jain +2

Toxicity identification in online multimodal environments remains a challenging task due to the complexity of contextual connections across modalities (e.g., textual and visual). I…

cs.AI2024★ 2 cited

Enhancing Cross-Modal Contextual Congruence for Crowdfunding Success using Knowledge-infused Learning

Trilok Padhi, Ugur Kursuncu, Yaman Kumar +2

The digital landscape continually evolves with multimodality, enriching the online experience for users. Creators and marketers aim to weave subtle contextual cues from various mod…