12 papers
ORBIT-FMIB: Tracking Order-Resolved Epistatic Information Through ESM-2
Maryam Rahimimovassagh, Ivan Garibay, Niloofar Yousefi
Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological interaction information rema…
Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations
Maryam Rahimimovassagh, Ivan Garibay, Niloofar Yousefi
Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Benchmarking of Interaction Tran…
BRIDGE: Bottleneck-Aware Regulator-Set Inference and Diagnosis for Cooperative Gene Regulatory Recovery
Maryam Rahimimovassagh, Clayton Thomas Barham, Ivan Garibay +1
Cooperative gene regulation often depends on groups of regulators acting jointly, but most gene regulatory network (GRN) inference methods output pairwise regulator-target rankings…
MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion
Tasfia Nuzhat Ornee, Elias Hossain, Ivan Garibay +1
Masked discrete diffusion for molecular graph generation typically applies a uniform corruption schedule to all tokens in a lossless graph-to-sequence representation, implicitly tr…
Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics
Maryam Rahimimovassagh, Md Elias Hossain, Ivan Garibay +1
Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational approaches reduce these dynami…
ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis
Mohammad Jahid Ibna Basher, Ali Khodabandeh Yalabadi, Ivan Garibay +1
Template based single step retrosynthesis predicts reactants by selecting and applying an explicit reaction template, making each prediction traceable to a chemical transformation…
When Policies Cannot Be Retrained: A Unified Closed-Form View of Post-Training Steering in Offline Reinforcement Learning
Elias Hossain, Mohammad Jahid Ibna Basher, Ivan Garibay +2
Offline reinforcement learning (RL) can learn effective policies from fixed datasets, but deployment objectives may change after training, and in many applications the trained acto…
UAT-LITE: Inference-Time Uncertainty-Aware Attention for Pretrained Transformers
Elias Hossain, Shubhashis Roy Dipta, Subash Neupane +4
Neural NLP models are often miscalibrated and overconfident, assigning high confidence to incorrect predictions and failing to express uncertainty during internal evidence aggregat…
BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in Antimicrobial Resistance
Elias Hossain, Mehrdad Shoeibi, Ivan Garibay +1
Interpreting gene clusters from RNA sequencing (RNA-seq) remains challenging, especially in antimicrobial resistance studies where mechanistic insight is important for hypothesis g…
Explainable Detection of Implicit Influential Patterns in Conversations via Data Augmentation
Sina Abdidizaji, Md Kowsher, Niloofar Yousefi +1
In the era of digitalization, as individuals increasingly rely on digital platforms for communication and news consumption, various actors employ linguistic strategies to influence…
User Profile with Large Language Models: Construction, Updating, and Benchmarking
Nusrat Jahan Prottasha, Md Kowsher, Hafijur Raman +4
User profile modeling plays a key role in personalized systems, as it requires building accurate profiles and updating them with new information. In this paper, we present two high…
Predicting Through Generation: Why Generation Is Better for Prediction
Md Kowsher, Nusrat Jahan Prottasha, Prakash Bhat +6
This paper argues that generating output tokens is more effective than using pooled representations for prediction tasks because token-level generation retains more mutual informat…