activity
20242026
collaborators

10 papers

cs.LG2026

VSPO: Vector-Steered Policy Optimization for Behavioral Control

Xuechen Zhang, Zijian Huang, Kai Yang +3

Modern language models often need to optimize a primary accuracy objective while also accommodating secondary behavioral preferences, such as verbosity, agreeableness, or the level…

cs.CL2026

Enabling Intrinsic Reasoning over Dense Geospatial Embeddings with DFR-Gemma

Xuechen Zhang, Aviv Slobodkin, Joydeep Paul +4

Representation learning for geospatial and spatio-temporal data plays a critical role in enabling general-purpose geospatial intelligence. Recent geospatial foundation models, such…

cs.LG2026

Continuous Chain of Thought Enables Parallel Exploration and Reasoning

Halil Alperen Gozeten, M. Emrullah Ildiz, Xuechen Zhang +3

Modern language models generate chain-of-thought traces by autoregressively sampling tokens from a finite vocabulary. While this discrete sampling has achieved remarkable success,…

cs.LG2026

Test-Time Training Provably Improves Transformers as In-context Learners

Halil Alperen Gozeten, M. Emrullah Ildiz, Xuechen Zhang +3

Test-time training (TTT) methods explicitly update the weights of a model to adapt to the specific test instance, and they have found success in a variety of settings, including mo…

cs.IR2025

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG

Xuechen Zhang, Koustava Goswami, Samet Oymak +2

Retrieval-augmented generation (RAG) has strong potential for producing accurate and factual outputs by combining language models (LMs) with evidence retrieved from large text corp…

cs.LG2025

BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning

Xuechen Zhang, Zijian Huang, Yingcong Li +3

Small language models (SLMs) struggle to learn complex reasoning behaviors, especially when high-quality traces are scarce or difficult to learn from. The standard training approac…