22 citations · 98 across the 20 of their papers we have counts for
23 papers
Selective Regenerative Decoding: Trajectory-Level Intervention for Inference-Time Reasoning
Sophia Xiao Pu, Yumo Xu, Sailik Sengupta +5
Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories, yet treat each trajectory as atomic: either retaining it whole or discarding it…
ε-Indistinguishability In Moving Target Defense: Framework, Algorithms, And Cloud Case Studies
Sailik Sengupta, Ankur Chowdhary
Moving Target Defense (MTD) assumes its pool of candidate configurations is safe to cycle among, i.e. latency and other observables do not trivially fingerprint the active choice,…
Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders
Yuwei Zhang, Siffi Singh, Sailik Sengupta +4
Conversational systems often rely on embedding models for intent classification and intent clustering tasks. The advent of Large Language Models (LLMs), which enable instructional…
FLAP: Flow-Adhering Planning with Constrained Decoding in LLMs
Shamik Roy, Sailik Sengupta, Daniele Bonadiman +2
Planning is a crucial task for agents in task oriented dialogs (TODs). Human agents typically resolve user issues by following predefined workflows, decomposing workflow steps into…
DeAL: Decoding-time Alignment for Large Language Models
James Y. Huang, Sailik Sengupta, Daniele Bonadiman +6
Large Language Models (LLMs) are nowadays expected to generate content aligned with human preferences. Current work focuses on alignment at model training time, through techniques…
Measuring and Mitigating Constraint Violations of In-Context Learning for Utterance-to-API Semantic Parsing
Shufan Wang, Sebastien Jean, Sailik Sengupta +3
In executable task-oriented semantic parsing, the system aims to translate users' utterances in natural language to machine-interpretable programs (API calls) that can be executed…