7 citations · 11 across the 5 of their papers we have counts for
6 papers
Multi-Modal Semantic Expansion with Constrained LLM Reranking for Conversational Music Recommendation
Naman Garg, Sarika Jain, George Fazekas
We present Team Semiintelligencn's solution for the ACM RecSys 2026 TalkPlayData Challenge, addressing conversational music recommendation through a multi-modal and personalized co…
KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction
Naman Garg, Sarika Jain, Sourav Yadav +4
While WGS-based AMR prediction has reached high accuracy, existing models lack a mechanism to ground neural attributions in established biological pathways. We present KG-TRACE, a…
REAL: Benchmarking Autonomous Agents on Deterministic Simulations of Real Websites
Divyansh Garg, Shaun VanWeelden, Diego Caples +15
We introduce REAL, a benchmark and framework for multi-turn agent evaluations on deterministic simulations of real-world websites. REAL comprises high-fidelity, deterministic repli…
Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Pranav Putta, Edmund Mills, Naman Garg +4
Large Language Models (LLMs) have shown remarkable capabilities in natural language tasks requiring complex reasoning, yet their application in agentic, multi-step reasoning within…
Recursive Introspection: Teaching Language Model Agents How to Self-Improve
Yuxiao Qu, Tianjun Zhang, Naman Garg +1
A central piece in enabling intelligent agentic behavior in foundation models is to make them capable of introspecting upon their behavior, reasoning, and correcting their mistakes…
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
Amrith Setlur, Saurabh Garg, Xinyang Geng +3
Training on model-generated synthetic data is a promising approach for finetuning LLMs, but it remains unclear when it helps or hurts. In this paper, we investigate this question f…